From maass@igi.tu-graz.ac.at Sun May 12 20:13:07 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id UAA11550 for ; Sun, 12 May 1996 20:13:01 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id UAA29053 for ; Sun, 12 May 1996 20:12:59 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa18477; 12 May 96 19:51:39 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa18475; 12 May 96 19:29:53 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa26831; 12 May 96 19:29:07 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa17802; 12 May 96 15:10:16 EDT Received: from figids03.tu-graz.ac.at by RI.CMU.EDU id aa24232; 12 May 96 15:10:11 EDT Received: from localhost by figids03.tu-graz.ac.at with SMTP id AA22731 (5.67b/IDA-1.5t for Connectionists@CS.CMU.EDU); Sun, 12 May 1996 21:11:18 +0200 Message-Id: <199605121911.AA22731@figids03.tu-graz.ac.at> To: Connectionists@cs.cmu.edu Subject: 2 papers in NEUROPROSE on spiking versus sigmoidal neurons Date: Sun, 12 May 96 21:11:12 +0200 From: Wolfgang Maass X-Mts: smtp 1) The file maass.third-generation.ps.Z is now available for copying from the Neuroprose repository. This is a 23-page long paper. Hardcopies are not available. FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/maass.third-generation.ps.Z Networks of Spiking Neurons: The Third Generation of Neural Network Models Wolfgang Maass Institute for Theoretical Computer Science Technische Universitaet Graz Klosterwiesgasse 32/2 A-8010 Graz, Austria e-mail: maass@igi.tu-graz.ac.at Abstract The computational power of formal models for networks of spiking neurons is compared with that of traditional neural network models based on McCulloch Pitts neurons (i.e. threshold gates) respectively sigmoidal gates. It is shown that networks of spiking neurons are computationally more powerful than threshold circuits and sigmoidal neural nets of the same size. A concrete biologically relevant function is exhibited which can be computed by a single spiking neuron (for biologically reasonable values of its parameters), but which requires hundreds of hidden units on a sigmoidal neural net. This article does not assume prior knowledge about spiking neurons, and it contains an extensive list of references to the currently available literature on computations in networks of spiking neurons and relevant results from neurobiology. *************************************************************** 2) The file maass.sigmoidal-spiking.ps.Z is now also available for copying from the Neuroprose repository. This is a 27-page long paper. Hardcopies are not available. FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/maass.sigmoidal-spiking.ps.Z An Efficient Implementation of Sigmoidal Neural Nets in Temporal Coding with Noisy Spiking Neurons Wolfgang Maass Institute for Theoretical Computer Science Technische Universitaet Graz Klosterwiesgasse 32/2 A-8010 Graz, Austria e-mail: maass@igi.tu-graz.ac.at Abstract We show that networks of spiking neurons can simulate arbitrary feedforward sigmoidal neural nets in a way which has previously not been considered. This new approach is based on temporal coding by single spikes (respectively by the timing of synchronous firing in pools of neurons), rather than on the traditional interpretation of analog variables in terms of firing rates. It is based on the observation that incoming "postsynaptic potentials" can SHIFT the firing time of a spiking neuron. The resulting new simulation is substantially faster and hence more consistent with experimental results about the speed of information processing in cortical neural systems. As a consequence we can show that networks of noisy spiking neurons are "universal approximators" in the sense that they can approximate with regard to temporal coding any given continuous function of several variables. This result holds for a fairly large class of schemes for coding analog variables by firing times of spiking neurons. Our new proposal for the possible organization of computations in networks of spiking neurons systems has some interesting consequences for the type of learning rules that would be needed to explain the self-organization of such networks. Finally, our fast and noise-robust implementation of sigmoidal neural nets via temporal coding points to possible new ways of implementing feedforward and recurrent sigmoidal neural nets with pulse stream VLSI. (To appear in Neural Computation.) From zhang@salk.edu Mon May 13 12:42:32 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id MAA23086 for ; Mon, 13 May 1996 12:42:26 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id MAA07332 for ; Mon, 13 May 1996 12:42:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa19497; 13 May 96 10:27:04 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa19495; 13 May 96 10:14:10 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa27447; 13 May 96 10:13:33 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa23276; 13 May 96 2:32:12 EDT Received: from helmholtz.salk.edu by CS.CMU.EDU id aa07105; 13 May 96 2:31:51 EDT Received: by salk.edu (4.1/SMI-4.1) id AA10324; Sun, 12 May 96 23:31:48 PDT From: Kechen Zhang Message-Id: <9605130631.AA10324@salk.edu> Subject: paper available: HD cell theory To: connectionists@cs.cmu.edu Date: Sun, 12 May 1996 23:31:47 -0700 (PDT) X-Mailer: ELM [version 2.4 PL22] Content-Type: text Content-Length: 3757 Paper available: HD cell theory http://www.cnl.salk.edu/~zhang/hd.ps.gz (30 pages, 0.4 Mb compressed) Frequently asked questions: What are head-direction (HD) cells? As with the hippocampal place cells, head-direction cells have been found in the brains of freely moving rats. These cells signal an animal's instantaneous directional heading in real space. Notice that here "real space" means real space. It is not the direction of the head relative to the shoulders or the body of the animal; instead, the system almost represents true compass direction in the sense that the preferred direction of a given cell remains the same in different surroundings (even in darkness). Do HD cells rely on geomagnetic cues to compute head direction? No, because rotation of familiar visual landmarks will typically lead to an equal rotation of the preferred directions of all head-direction cells. Then, how do HD cells know the true head direction? The exact mechanisms are still unknown, although there are several theoretical proposals. >From a theoretical point of view, the HD cell system is very interesting. It provides compelling neurobiological evidence for the existence of stable attractor dynamics; at the same time, it forces consideration of the challenging problem of how to shift a stable activity profile. Because the first systematic experimental studies of HD cells were published only in 1990, the current paper includes a relatively complete reference list of the experimental publications, in addition to some immediately related theoretical papers. ____________________________________________________________________________ The paper has appeared in: Journal of Neuroscience 16(6): 2112-2126 (1996) Title: Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: A theory Author: Kechen Zhang Department of Cognitive Science University of California, San Diego La Jolla, California 92093-0515 Abstract: The head-direction (HD) cells found in the limbic system in freely moving rats represent the instantaneous head direction of the animal in the horizontal plane regardless of the location of the animal. The internal direction represented by these cells uses both self-motion information for inertially based updating and familiar visual landmarks for calibration. Here, a model of the dynamics of the HD cell ensemble is presented. The stability of a localized static activity profile in the network and a dynamic shift mechanism are explained naturally by synaptic weight distribution components with even and odd symmetry, respectively. Under symmetric weights or symmetric reciprocal connections, a stable activity profile close to the known directional tuning curves will emerge. By adding a slight asymmetry to the weights, the activity profile will shift continuously without disturbances to its shape, and the shift speed can be accurately controlled by the strength of the odd-weight component. The generic formulation of the shift mechanism is determined uniquely within the current theoretical framework. The attractor dynamics of the system ensures modality-independence of the internal representation and facilitates the correction for cumulative error by the putative local- view detectors. The model offers a specific one-dimensional example of a computational mechanism in which a truly world-centered representation can be derived from observer-centered sensory inputs by integrating self- motion information. __________________________________________________________________________ Comments and suggestions are welcome. Email: zhang@salk.edu or kzhang@cogsci.ucsd.edu http://www.cnl.salk.edu/~zhang From tbl@di.ufpe.br Mon May 13 19:44:42 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id TAA00592 for ; Mon, 13 May 1996 19:44:37 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id TAA14344 for ; Mon, 13 May 1996 19:44:35 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa19745; 13 May 96 15:48:25 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa19743; 13 May 96 15:35:26 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa27569; 13 May 96 15:35:19 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id ab01932; 13 May 96 15:13:38 EDT Received: from recife.di.ufpe.br by CS.CMU.EDU id aa12082; 13 May 96 15:13:13 EDT Received: from pesqueira (pesqueira.di.ufpe.br) by di.ufpe.br (4.1/SMI-4.1) id AA16782; Mon, 13 May 96 16:14:01 EST Received: by pesqueira (5.x/SMI-SVR4) id AA05844; Mon, 13 May 1996 16:13:32 -0300 Date: Mon, 13 May 1996 16:13:32 -0300 From: tbl@di.ufpe.br Message-Id: <9605131913.AA05844@pesqueira> To: Connectionists@cs.cmu.edu Subject: call for papers III Brazilian Symposium on Neural Networks ****************************************** First call for papers Sponsored by the Brazilian Computer Society (SBC) The Third Brazilian Symposium on Neural Networks will be held at the Federal University of Pernambuco, in Recife (Brazil), from the 12nd to the 14th of November, 1996. The SBRN symposia, as they were initially named, are organized by the interest group in Neural Networks of the Brazilian Computer Society since 1994. The third version of the meeting follows a very successfull organization of the previous events which brought together the main developments of the area in Brazil and had the participation of many national and international researchers both as invited speakers and as authors of papers presented at the symposium. Recife is a very pleasant city in the northeast of Brazil, known by its good climate and beautiful beaches, with sunshine throughout almost the whole year. The city, whose name originated from the coral formations in the seaside port and beaches, is in a strategic touristic situation in the region and offers a good variety of hotels both in the city historic center and at the seaside resort. Scientific papers will be analyzed by the program committee. This analysis will take into account originality, significance to the area, and clarity. Accepted papers will be fully published in the conference proceedings. The major topics of interest include, but are not limited to: Biological Perspectives Theoretical Models Algorithms and Architectures Learning Models Hardware Implementation Signal Processing Robotics and Control Parallel and Distributed Implementations Pattern Recognition Image Processing Optimization Cognitive Science Hybrid Systems Dynamic Systems Genetic Algorithms Fuzzy Logic Applications Program Committee: (Tentative) - Teresa Bernarda Ludermir - DI/UFPE - Andre C. P. L. F. de Carvalho - ICMSC/USP (chair) - Germano C. Vasconcelos - DI/UFPE - Antonio de Padua Braga - DEE/UFMG - Dibio Leandro Borges - CEFET/PR - Paulo Martins Engel - II/UFRGS - Ricardo Machado - PUC/Rio - Valmir Barbosa - COPPE/UFRJ - Weber Martins - EEE/UFG Organising Committee: - Teresa Bernarda Ludermir - DI/UFPE (chair) - Edson C. B. Carvalho Filho - DI/UFPE - Germano C. Vasconcelos - DI/UFPE - Paulo Jorge Leitao Adeodato- DI/UFPE SUBMISSION PROCEDURE: The symposium seeks contributions to the state of the art and future perspectives of Neural Networks research. Submitted papers must be in Portuguese, English or Spanish. The submissions must include the original and three copies of the paper and must follow the format below (Electronic mail and FAX submissions are NOT accepted). The paper must be printed using a laser printer, in two-column format, not numbered, 8.5 X 11.0 inch (21,7 X 28.0 cm). It must not exceed eight pages, including all figures and diagrams. The font size should be 10 pts, such as Times-Roman or equivalent, with the following margins: right and left 2.5 cm, top 3.5 cm, and bottom 2.0 cm. The first page should contain the paper's title, the complete author(s) name(s), affiliation(s), and mailing address(es), followed by a short (150 words) abstract and a list of descriptive key words. The submission should also include an accompanying letter containing the following information : * Manuscript title * First author's name, mailing address and e-mail * Technical area of the paper SUBMISSION ADDRESS: Four copies (one original and three copies) must be submitted to: Andre C. P. L. F. de Carvalho Coordenador do Comite de Programa - III SBRN Departamento de Ciencias de Computacao e Estatistica ICMSC - Universidade de Sao Paulo Caixa Postal 668 CEP 13560.070 Sao Carlos, SP Brazil Phone: +55 162 726222 FAX: +55 162 749150 E-mail: IIISBRN@di.ufpe.br IMPORTANT DATES: August 16, 1996 (mailing date) Deadline for paper submission September 16, 1996 Notification of acceptance/rejection November, 12-14 1996 III SBRN ADDITIONAL INFORMATION: * Up-to-minute information about the symposium is available on the World Wide Web (WWW) at http://www.di.ufpe.br/~IIISBRN/web_sbrn * Questions can be sent by E-mail to IIISBRN@di.ufpe.br We look forward to seeing you in Recife ! From pazzani@super-pan.ICS.UCI.EDU Mon May 13 20:20:25 1996 Received: from cs.wisc.edu (cs.wisc.edu [128.105.2.6]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id UAA00836 for ; Mon, 13 May 1996 20:20:05 -0500 Received: from paris.ics.uci.edu (paris.ics.uci.edu [128.195.1.50]) by cs.wisc.edu (8.6.12/8.6.12) with SMTP id UAA08027; Mon, 13 May 1996 20:19:11 -0500 Received: from super-pan.ics.uci.edu by paris.ics.uci.edu id aa03547; 13 May 96 14:06 PDT To: ML-LIST:; Subject: Machine Learning List: Vol. 8, No. 9 Reply-to: ml@ics.uci.edu Date: Mon, 13 May 1996 13:41:18 -0700 From: Michael Pazzani Message-ID: <9605131406.aa03547@paris.ics.uci.edu> Machine Learning List: Vol. 8, No. 9 Monday, May 13, 1996 Contents: ILP'96 REMINDER: NIPS*96 SUBMISSION DEADLINE Hypertext Bibliographies for Machine Learning Call for Demos for KDD-96 Applied Research and Evaluation of Conference Submissions Special Issue of the Journal "Artificial Intelligence in Medicine" Call for Papers for PAKDD97 KBCS-96 International Conference on Knowledge Based Computer Systems New IDSIA/TUM papers available Call for Papers: Fuzzy-Neuro Systems '97 IDA97 announcement CFP: Rough Sets and Soft Computing, 1997 GP-96 Registration and Papers Research Students Wanted The Machine Learning List is moderated. Contributions should be relevant to the scientific study of machine learning. Mail contributions to ml@ics.uci.edu. Mail requests to be added or deleted to ml-request@ics.uci.edu. Back issues may be obtained from http://www.ics.uci.edu/AI/ML/Machine-Learning.html ---------------------------------------------------------------------- Date: Fri, 3 May 96 15:10:57 BST From: David Page Subject: ILP'96 SIXTH INTERNATIONAL WORKSHOP ON INDUCTIVE LOGIC PROGRAMMING (ILP'96) REMINDER This is a reminder that the deadline for submissions to ILP'96 is May 17. Please send 3 copies of each submission. Also, please note that there are no format requirements or length restrictions on submissions, although the final copies must be in Latex and format specifications will be provided. ------------------------------ Date: Wed, 8 May 1996 13:25:00 -0400 (EDT) From: Sue Becker Subject: REMINDER: NIPS*96 SUBMISSION DEADLINE This is to remind you that the deadlines for paper submissions (May 24) and workshop proposals (May 20) for the Neural Information Processing Systems -- Natural and Synthetic conference are rapidly approaching. The calls for papers and workshop proposals and style files can be retrieved from the NIPS web page: http://www.cs.cmu.edu/Web/Groups/NIPS Sue Becker Publicity Chair, NIPS*96 ------------------------------ Date: Thu, 9 May 1996 09:05:39 -0400 From: Peter Turney Subject: Hypertext Bibliographies for Machine Learning Hypertext Bibliographies for Machine Learning A new hypertext bibliography (with hyperlinks to the authors and the papers) on "Feature Selection" has been added to the collection of "Hypertext Bibliographies for Machine Learning". Any coments, corrections, or additions are welcome. Feature Selection http://ai.iit.nrc.ca/bibliographies/feature-selection.html Hypertext Bibliographies for Machine Learning http://ai.iit.nrc.ca/bibliographies/ Sincerely, Peter Turney, peter@ai.iit.nrc.ca ------------------------------ Date: Fri, 10 May 1996 10:44:27 -0700 (PDT) From: KDD-96 Account Subject: Call for Demos for KDD-96 In conjunction with the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), to be held August 2-4, 1996 in Portland, Oregon we are inviting demonstrations of Knowledge Discovery Systems and Applications. This is an excellent opportunity to demonstrate to a large number of active researchers, developers and users in the field of Knowledge Discovery. Full details are available at http://www-aig.jpl.nasa.gov/kdd96/cfd.html The deadline date is June 3rd. ------------------------------ Date: Fri, 3 May 1996 17:17:26 -0500 (CDT) From: Eduardo Perez Subject: Applied Research and Evaluation of Conference Submissions The importance Machine Learning applied research cannot be emphasized enough. At the same time, it is equally important to maintain high standards for evaluating all research submitted for publication. Some have recently expressed discontent regarding the interplay of these two important aspects in our research community. I make two suggestions that may help to reduce such discontents in the future. Both suggestions overlap partially with previous comments made in this list, but these are more precise: (1) The AAAI Review Criteria made public with the call for papers closely match (and quite possibly are identical to) the questions that reviewers have to answer in evaluating submissions. However, the same does not seem true for ICML (note the unspecified year). Reviewers are asked questions far more specific than what was given to the public as the conference review criteria in the call for papers. The suggestion is that, inasmuch as possible, ICML announce publicly the review criteria that the program committee members will be actually asked to follow. (2) Machine Learning is not the only field to have experienced the discontent mentioned above. Among many publications listed in the WWW site titled ``Advice on Research and Writing'' (http://www.cs.cmu.edu/afs/cs.cmu.edu/user/mleone/web/how-to.html), there are a few written by program committee members of conferences in fields such as Operating Systems and Programming Languages. These program committee members discuss their recent participation on the reviewing process for a specific conference. They offer reflections on the quality of the process as a whole: input, procedure and outcome, as well as recommendations on how to avoid important pitfalls frequent among rejected submissions. The suggestion is that senior members of program committees in Machine Learning, Artificial Intelligence, and related fields, write reflections and recommendations like those mentioned above. Eduardo Perez Beckman Institute & Dept. of Computer Science University of Illinois at Urbana-Champaign 405 North Mathews Avenue, Urbana, IL 61801, U.S.A. +1(217)244-5915 +1(217)244-8317 Fax ------------------------------ Date: Fri, 10 May 1996 18:15:39 +0100 From: Jim Hunter Subject: Special Issue of the Journal "Artificial Intelligence in Medicine" CALL FOR SUBMISSIONS Special Issue of the Journal "Artificial Intelligence in Medicine" DECISION SUPPORT IN THE OPERATING THEATRE AND INTENSIVE CARE Guest-Editor: Jim Hunter (University of Aberdeen) [Apologies if you receive multiple copies of this] The operating theatre and the intensive care (or therapy) unit (ICU) provide environments which pose particular challenges for decision support in clinical medicine. Considerable volumes of clinical patient data are available there with the possibility of measuring many variables (particularly those relating to the cardiovascular and respiratory systems) on a continuous basis. However the provision of so much data to clinicians and nurses brings its own problems of data overload, false positive alarms etc. Other challenges include high rates of intervention, obviously including surgical procedures, but also ventilation, drugs, fluids, etc. Furthermore it is likely (particularly in the ICU) that the clinical decision making may be extremely complex, with patients suffering from multiple system failure. The last special issue of Artificial Intelligence in Medicine relating to the ICU was published in 1992 and five years further on it seems appropriate to review developments over that period. The aim of this special issue (to appear in 1997) is to bring together papers describing the use of knowledge to help manage the information available in these data rich environments. Because of the emphasis on the domain, it is expected that submissions will tend to be of an applied nature; however papers which deal with more theoretical aspects can be submitted provided that their relevance to the domain is clear. Decision support can be provided in a number of ways, including systems which: - monitor patient data in the background and raise real-time alarms; - support the configuration of data displays; - critique or propose the administration of drugs and other therapeutic interventions; - abstract and summarise patient state; - collate information for later use (e.g. in discharge letters and for audit); - etc. These can be based on a number of AI technologies including: - symbolic reasoning (e.g. rules and frames); - sub-symbolic reasoning (e.g. neural nets, genetic algorithms); - qualitative and semi-quantitative models; - temporal reasoning; - various ways of dealing with uncertainty; - planning; - machine learning; - natural language generation; - etc. These applications and technologies are indicative and not meant to exclude others. It is expected that the special issue will contain 4-5 papers of 20-25 manuscript pages each. Manuscripts should be typed on good quality paper of uniform size (A4 or 8.5 by 11 inches), double-spaced with wide margins of at least 3 cm. Each manuscript should include the title of the contribution, the author's or authors' name(s), complete address(es), e-mail address(es), fax and telephone numbers, an abstract of about 100 words accompanied by a list of a few keywords, consecutively numbered sections with headings and references. A manuscript should never exceed 40 pages. Complete submission guidelines are available upon request from the guest editor. Potential authors should send three copies of their manuscripts by September 1, 1996 to: Dr Jim Hunter Department of Computing Science University of Aberdeen King's College ABERDEEN AB24 3UE UNITED KINGDOM Phone: +44 (0)1224 272287 FAX: +44 (0)1224 273422 email: jhunter@csd.abdn.ac.uk WWW: http://www.csd.abdn.ac.uk/ It would be helpful to the guest editor if intending contributors could submit a tentative title and abstract by June 15, 1966. All manuscripts submitted will be subject to a rigorous review process. It expected that decisions on acceptance/rejection will be made by December 1, 1996; the final versions of revised papers are due by February 15, 1997. It is expected that the issue will appear in September 1997. SUMMARY OF SCHEDULE June 15, 1996 Submission of tentative title/abstract September 1, 1996 Submission of manuscripts December 1, 1996 Notification of acceptance/rejection February 15, 1997 Submission of final versions of papers September, 1997 Publication of special issue A copy of this announcement and complete submission guidelines are available on the WWW at: http://www.csd.abdn.ac.uk/~jhunter/AIM_call.html ------------------------------ Date: Thu, 2 May 1996 12:06:01 +0800 (GMT-8) From: Liu Huan Subject: Call for Papers for PAKDD97 FIRST PACIFIC-ASIA CONFERENCE on KNOWLEDGE DISCOVERY and DATA MINING (PAKDD97) Singapore, 23-24 February, 1997 (Co-located with 2nd Pacific-Asia Conference on Expert Systems/ 3rd Singapore International Conference on Intelligent Systems) The first Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD97) will be held in Singapore. As the range of computer applications is broadening, more and more data is captured and/or generated. In order to overcome the situation of ``data rich and knowledge poor'', knowledge discovery and data mining (KDD) is becoming the focus of many fields from Intelligent Databases, Machine Learning to Statistics. The aims of the conference are to cover all aspects of KDD, to bring together researchers and practitioners from basic and applied research and information industries, and to push forward the state-of-art of KDD. The conference technical programme will include paper presentations, posters, invited talks, and tutorials in a two-day event. Areas of interest include, but are not limited to: Knowledge Representation and Acquisition in KDD Data Mining and Data Warehousing Data Cleaning, Preprocessing and Postprocessing Data and Dimensionality Reduction Knowledge Reuse and Role of Domain Knowledge Data Mining Tools KDD Framework and Process Security and Privacy Issues in KDD Mining in-the-Large vs Mining in-the-Small Management Issues in KDD Machine Learning, Statistical and Visualization Aspects of KDD Successful/Innovative Applications in Science, Government, Business and Industry The proceedings will be published by an international publisher and will be available at the conference. PAKDD is Organized by Information Technology Institute & National University of Singapore in Cooperation with National Computer Board, Singapore Singapore Computer Society AI Chapter Japanese Society for Artificial Intelligence Korea Advanced Institute of Science & Technology Korea Expert Systems Society Submission Information: Tutorial proposal comprising summary, course outline and a brief biography of the speaker(s); 4 copies of full paper (3000-5000 words) 4 copies of applications paper (about 3000 words) Submission Address: Dr. Hongjun Lu Department of ISCS National University of Singapore Kent Ridge, Singapore 119260 For further information, please contact pakdd97@iti.gov.sg or check the conference web site: http://www.iscs.nus.sg/conferences/pakdd97.html. Important Dates: 1 Aug., 1996 for submission of papers and proposals 15 Oct., 1996 for notification of acceptance 15 Dec., 1996 for receipt of camera-ready manuscripts Conference General Chair: Hing-Yan Lee, Japan-Singapore AI Centre (JSAIC), Information Technology Institute Organizing Committee: Lynica Foo, JSAIC, Kwok-Leong Hui, JSAIC Bing Liu, National U. of S'pore (NUS) Hwee-Leng Ong, JSAIC Angeline Pang, JSAIC Publicity Chair: Huan Liu, NUS Programme Co-Chairs: Hongjun Lu Hiroshi Motoda Dept of Info. Sys. & Comp. Sci. Institute of Sci. & Indus. Research National University of Singapore Osaka University, Japan Related Conferences: ISIS
------------------------------ Subject: KBCS-96 International Conference on Knowledge Based Computer Systems Date: Mon, 13 May 1996 11:22:56 -0500 From: KBCS96 Call for Papers INTERNATIONAL CONFERENCE ON KNOWLEDGE BASED COMPUTER SYSTEMS National Centre for Software Technology Bombay, India December 16-18, 1996 URL : http://konark.ncst.ernet.in/~kbcs/kbcs96.html The International Conference on Knowledge Based Computer Systems will be held in Bombay, India during December 16-18, 1996. The conference is intended to act as a forum for promoting interaction among researchers in the field of Artificial Intelligence in India and abroad. There will be a two day conference during December 16-17, 1996 followed by one day of post-conference tutorials on December 18, 1996. Papers are invited on substantial, original and unpublished research on all aspects of Artificial Intelligence, including, but not limited to the following: o AI Applications o AI Architectures o Artificial Life o Automatic Programming o Cognitive Modeling o Expert Systems o Foundations of AI o Genetic Algorithms o Information Retrieval o Intelligent Tutoring Systems o Knowledge Acquisition o Knowledge Representation o Machine Learning o Machine Translation o Natural Language Processing o Neural Networks o Planning and Scheduling o Reasoning o Robotics o Search Techniques o Speech Processing o Theorem Proving o Uncertainty Handling o User Interfaces o User Modeling o Vision Format of Submission: Authors should submit their papers, not to exceed 5000 words (including figures and references) either electronically or in hard copy. Papers should be in English. Papers should include an abstract of about 100-200 words in length. Papers outside the specified length are subject to rejection without review. Since reviewing will be "blind", the authors' names and affiliations along with the main area of the paper should be given only on a separate cover sheet. Hard copy submissions should be sent in triplicate. Papers in electronic form can be in any of the following formats: plain text, Postscript, Latex, Microsoft Word (RTF format) or Wordstar. Submissions in electronic form are preferred. Send papers to the KBCS-96 Secretariat at the address below. Paper Submission Deadlines: o Papers due: July 31, 1996 o Acceptance Notification: October 15, 1996 o Camera Ready Copy due: December 1, 1996 Call for Tutorials: Proposals are invited for post-conference tutorials. Tutorials can be half-day or full-day, and will be held on December 18th, 1996. The proposal should be presented in the form of a 200-word abstract, one page topical outline of the content, description of the proposers and their qualifications relating to the tutorial content. Tutorial Submission Deadlines: o Proposal Submission: July 31, 1996 o Acceptance Notification: August 31, 1996 o Complete Tutorial materials due: December 1, 1996 Send proposals to the KBCS-96 Secretariat at the address below. Organizing Committee: George Arakal, NCST (Chair) K.S.R. Anjaneyulu, NCST P. Ravi Prakash, NCST Durgesh D. Rao, NCST M. Sasikumar, NCST T. Suresh, NCST For further information please refer to the KBCS-96 home page or write to the KBCS-96 Secretariat. Address KBCS-96 Secretariat Phone : +91 (22) 620 1606 National Centre for Software Technology Fax : +91 (22) 621 0139 Gulmohar Cross Rd No. 9 E-mail : kbcs@konark.ncst.ernet.in Juhu, Bombay 400 049, India URL : http://konark.ncst.ernet.in/~kbcs/kbcs96.html ------------------------------ From: Juergen Schmidhuber Date: Mon, 13 May 1996 12:14:40 +0200 Subject: New IDSIA/TUM papers available New IDSIA/TUM papers available - to obtain copies, cut and paste: netscape http://www.idsia.ch/~juergen/onlinepub.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~- FLAT MINIMA To appear in Neural Computation (accepted 1996) 38 pages, 154 K compressed, 463 K uncompressed Sepp Hochreiter, TUM Juergen Schmidhuber We present a new algorithm for finding low-complexity neural networks with high generalization capability. The algorithm searches for a ``flat'' minimum of the error function. A flat minimum is a large connected region in weight-space where the error remains approximately constant. An MDL-based, Bayesian argument suggests that flat minima correspond to ``simple'' networks and low expected overfitting. The argument is based on a Gibbs algorithm variant and a novel way of splitting generalization error into underfitting and overfitting error. Unlike many previous approaches, ours does not require Gauss- assumptions and does not depend on a ``good'' weight prior - instead we have a prior over input/output functions, thus ta- king into account net architecture and training set. Although our algorithm requires the computation of second order deri- vatives, it has backprop's order of complexity. Automatically, it effectively prunes units, weights, and input lines. Expe- riments with feedforward and recurrent nets are described. In applications to stock market prediction, flat minimum search outperforms conventional backprop, weight decay, ``optimal brain surgeon'' / ``optimal brain damage''. We also provide pseudo code of the algorithm (omitted from the NC-version). Also available at http://www7.informatik.tu-muenchen.de/~hochreit/pub.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SEQUENTIAL NEURAL TEXT COMPRESSION (9 pages, 68 K) IEEE Transactions on Neural Networks, 7(1):142-146, 1996 Juergen Schmidhuber Stefan Heil, TUM Abstract: Neural nets may be promising tools for loss-free data compression. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to short newspaper articles and obtain compression ratios ex- ceeding those of widely used Lempel-Ziv algorithms (the basis of UNIX functions `compress' and `gzip'). The main disadvantage of our methods is: on conventional machines they are about 3 orders of magnitude slower than standard methods. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SEMILINEAR PREDICTABILITY MINIMIZATION PRODUCES WELL-KNOWN FEATURE DETECTORS Neural Computation, 1996 (accepted) (9 pages, 260 K compressed, 1.14 M uncompressed) Juergen Schmidhuber Martin Eldracher Bernhard Foltin Predictability minimization (PM) exhibits various intuitive and theoretical advantages over many other methods for unsupervised redundancy reduction. So far, however, there were only toy applications of PM. In this paper, we apply semilinear PM to static real world images and find: without teacher and without any significant pre-processing, the system automatically learns to generate distributed representations based on well-known feature detectors, such as orientation sensitive edge detectors and off-center-on-surround-like structures, thus extracting simple features related to those considered useful for image pre-processing and compression. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SOLVING POMDPs WITH LEVIN SEARCH AND EIRA 9 pages, 86K compressed, 252K uncompressed Machine Learning: 13th Intern. Conf., 1996 Marco Wiering Juergen Schmidhuber Partially observable Markov decision problems (POMDPs) recently received a lot of attention in the reinforcement learning community. No attention, however, has been paid to Levin's universal search through program space (LS), which is theoretically optimal for a wide variety of search prob- lems including many POMDPs. Experiments in this paper show that LS can solve partially observable mazes (`POMS') involving many more states and obstacles than those solved by various previous authors. We then note, however, that LS is not necessarily optimal for learning problems where experience with previous problems can be used to speed up the search. For this reason, we introduce an adaptive extension of LS (ALS) which uses experience to increase probabilities of instructions occurring in successful programs found by LS. To deal with cases where ALS does not lead to long-term performance improvement, we use the recent technique ``environment-independent reinforcement acceleration'' (EIRA) as a safe- ty belt (EIRA currently is the only known method that guarantees a life- long history of reward accelerations). Additional experiments demon- strate: (a) ALS can dramatically reduce search time consumed by success- ive calls of LS. (b) Further significant speed-ups can be obtained by combining ALS and EIRA. Also available at http://www.idsia.ch/~marco/publications.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Juergen Schmidhuber research director IDSIA, Corso Elvezia 36, 6900-Lugano, Switzerland juergen@idsia.ch http://www.idsia.ch/~juergen ------------------------------ Date: Fri, 3 May 1996 14:13:39 +0100 (DFT) From: FNS 97 Subject: Call for Papers: Fuzzy-Neuro Systems '97 CALL FOR PAPERS Fuzzy-Neuro Systems '97 - Computational Intelligence - 4th International Workshop 12 to 14 March 1997 University of Paderborn, Germany Fuzzy-Neuro Systems '97 is the fourth event of a well established series of workshops with international participation. Its aim is to give an overview of the state of the art in research and development of fuzzy systems and artificial neural networks. Another aim is to highlight applications of these methods and to forge innovative links between theory and application by means of creative discussions. Fuzzy-Neuro Systems '97 will add evolutionary algorithms to the areas of fuzzy logic and neural networks in order to show current trends in soft computing and computational intelligence comprehensively. Interested parties are especially encouraged to hand in contributions of hybrid systems that combine advantages of various methods efficiently. Organizer of this workshop is Research Committee 1.2 "Inference Systems" (Fachausschuss 1.2 "Inferenzsysteme") of German Society of Computer Science (Gesellschaft fuer Informatik e. V. (GI)) supported by Research Center "Sensors/Actuators" (Forschungsschwerpunkt "Sensorik/Aktorik") of Northrhine- Westfalia (Nordrhein-Westfalen) at University of Paderborn, Department Soest. Preceding workshops were held in Braunschweig (1993), Munich (1994) and Darmstadt (1995). Invited plenary speakers were Prof. D. Dubois (Toulouse), Prof. J. A. Feldman (Berkeley), Dr. H. Hellendoorn (Munich), Prof. L. Koczy (Tokyo, Budapest), Prof. R. Kruse (Braunschweig), Prof. E. H. Mamdani (London), Prof. L. A. Zadeh (Berkeley) and Prof. H.-J. Zimmermann (Aachen). Invited plenary speakers for this workshop will be Prof. J. Bezdek (Pensacola), Prof. E. P. Klement (Linz), Prof. T. Kohonen (Helsinki), Prof. W. Pedrycz (Manitoba) and Prof. H.-P. Schwefel (Dortmund). Conference languages will be German and English. Further information is available in World Wide Web under http://www.uni-paderborn.de/~fns97/ Scientific Topics _________________ - theory and principles of multivariate and fuzzy logic - representation modes of fuzzy knowledge - approximate reasoning - fuzzy control: theory and practice - fuzzy logic: data analysis, signal processing and pattern recognition - fuzzy classification systems - fuzzy decision support systems - fuzzy logic in non-technical areas: business administration, management etc. - fuzzy databases - theorie and principles of artificial neural networks - hybrid learning algorithms - neural networks: pattern recognition, classification, process monitoring and production control - theory and principles of evolutionary algorithms: genetic algorithms and evolution strategies - discrete parameter and structural optimization - hybrid systems: neuro-fuzzy systems, connectionistic expert systems etc. - special hardware and software Submission of Contributions ___________________________ Please pay attention to the following deadlines for submission of contributions: 30/08/1996: abridged version (German or English, 3 to 4 pages DIN A4 size) of following structure: - title - author(s) - address - phone - fax - e-mail Contents: 1. abstract 2. key words (not more than 5) 3. state of the art 4. new aspects 5. theory, simulation or experiment 6. results and conclusion 7. references October 96: notification of acceptance or rejection of contribution 29/11/1996: final camera-ready papers for proceedings (up to 8 pages DIN A4) Please send your scientific contribution in four copies to: Prof. Dr. Adolf Grauel Universitaet-Gesamthochschule Paderborn Abteilung Soest, Fachbereich 16 Fachgebiet Mathematische Methoden und Systemtheorie Steingraben 21 D-59494 Soest GERMANY WWW: http://www.uni-paderborn.de/~fns97/ E-mail: fns97@uni-paderborn.de Workshop Fees Workshop fees are: industry rate DM 600,- university rate DM 450,- rate for GI members or speakers DM 400,- rate for students without income DM 100,- (excluding proceedings and banquet) A surcharge of DM 100,- is payable for registration after 15/2/1996. Services of Gesellschaft fuer Informatik e. V. (GI) are tax-free according to German law 4 Nr. 22a UStG. The fee includes proceedings, drinks during breaks as well as DM 45,- for attending the banquet. DM 45,- incl. VAT paid for the banquet will be directly remitted to the account of a local caterer. Registration Please send the completed application form to: DLGI Dienstleistungsgesellschaft fuer Informatik mbH Frau Gabriele Trapp Ahrstrasse 45 D-53175 Bonn GERMANY Phone: ++ 49 / 2 28 / 30 21 64 Fax: ++ 49 / 2 28 / 37 86 90 Application Form I am interested in (please tick) O submitting a contribution; O attending the workshop. Last name:__________________________________________________________________ First name:_________________________________________________________________ Title:______________________________________________________________________ Affiliation:________________________________________________________________ Address:____________________________________________________________________ ____________________________________________________________________________ ____________________________________________________________________________ Phone:______________________________________________________________________ Fax:________________________________________________________________________ E-mail:_____________________________________________________________________ GI member number:___________________________________________________________ Place/Date:_________________________________________________________________ Signature:__________________________________________________________________ ------------------------------ Date: Thu, 2 May 1996 15:06:03 +0200 From: Michael Berthold Subject: IDA97 announcement Announcing IDA-97: Second International Symposium on Intelligent Data Analysis Birkbeck College, London 4th-6th August 1997 Objective ========= For many years the intersection of computing and data analysis contained menu-based statistics packages and not much else. Recently, statisticians have embraced computing, computer scientists are using statistical theories and methods, and researchers in all corners are inventing algorithms to find structure in vast online datasets. Data analysts now have access to tools for exploratory data analysis, decision tree induction, causal induction, function finding, constructing customised reference distributions, and visualisation. There are prototype intelligent assistants to advise on matters of design and analysis. There are tools for traditional, relatively small samples and for enormous datasets. The focus of IDA-97 will be "Reasoning About Data". We are interested in intelligent systems that reason about how to analyze data, perhaps as human analysts do. Analysts often bring exogenous knowledge about data to bear when they decide how to analyze it; they use intermediate results to decide how to proceed; they reason about how much analysis the data will actually support; they consider which methods will be most informative; they decide which aspects of a model are most uncertain and focus attention there; they sometimes have the luxury of collecting more data, and plan to do so efficiently. In short, there is a strategic aspect to data analysis, beyond the tactical choice of this or that test, visualisation or variable. IDA-95, the First International Symposium on Intelligent Data Analysis, was organised to provide an international forum for the discussion of such issues. The symposium took place in Germany and attracted participants from 20 countries in four continents. A survey after the event supported the idea of making IDA a regular, biennial conference. IDA-97 will be a major international, high-quality meeting that brings together a broad spectrum of work. Topics ====== The following topics are of particular interest to IDA-97: - Analysis of IDA algorithms - applications (e.g., commerce, engineering, finance, legal, manufacturing, medicine, public policy, science) - assistants, intelligent agents for data analysis - Bayesian inference and influence diagrams - bias - bootstrap, randomization, computer-intensive methods - causal modeling - censored data - classification - clustering - data mining - data visualisation - data cleaning, pre-processing and post-processing - decision analysis - evaluation of IDA systems - exploratory data analysis - experiment design - fuzzy logic - graphical models - human-computer interaction in IDA - information extraction, information retrieval, textual systems - knowledge-based systems - machine learning and statistics - model specification, selection, estimation - neural/evolutionary approaches - reasoning under uncertainty - representation of statistical knowledge - search - statistical pattern recognition - statistical strategy - time series and temporal data - uncertainty and noise in data - visualization Submissions =========== We are still working on the submission details and we shall make them available in the next call for papers and on the IDA-97 WWW pages. Review ====== All submissions will be reviewed on the basis of relevance, originality, significance, soundness and clarity. At least two referees will review each submission independently and final decisions will be made by program chairs, in consultation with relevant reviewers. Publications ============ Papers which are accepted and presented at the conference will appear in the IDA-97 proceedings. Authors of the best papers will be invited to extend their papers for inclusion in a special issue of "Intelligent Data Analysis: An International Journal". Location ======== IDA-97 will be held in the newly-furnished conference halls at Birkbeck College, University of London. The college is ranked among the leading UK university institutions for its levels of national and international excellence in research in the humanities, natural sciences and social sciences. It is situated in central London, surrounded by many of the well-known museums, theatres, restaurants, and shops. It is directly reachable from Heathrow airport, in about 50 minutes by London Underground. Exhibitions =========== IDA-97 welcomes demonstrations of software and publications related to intelligent data analysis. Sponsorship =========== IDA-97 welcomes those organisations who may wish to partly sponsor the conference. Sponsorship of an international conference in an important emerging field such as IDA-97 will ensure high visibility for the benefactor, both through the appearance of the organisation logo on promotional literature and in references to the conference in all media exposure prior to and after the event. IDA-97 Organisation =================== General Chair: Xiaohui Liu Program Chairs: Paul Cohen, Xiaohui Liu Steering Comm. Chair: Paul Cohen, University of Massachusetts, USA Exhibition Chair: Richard Weber, MIT GmbH, Aachen, Germany Finance Chair: Sylvie Jami, Birkbeck College, UK Local Arrangements Chair: Trevor Fenner, Birkbeck College, UK Public. and Proc. Chair: Michael Berthold, University of Karlsruhe, Germany Sponsorship Chair: Mihaela Ulieru, Simon Fraser University, Canada Steering Committee Michael Berthold University of Karlsruhe, Germany Fazel Famili National Research Council, Canada Doug Fisher Vanderbilt University, USA Alex Gammerman Royal Holloway London, UK David Hand Open University, UK Wenling Hsu AT&T Research, USA Xiaohui Liu Birkbeck College, UK Daryl Pregibon AT&T Research, USA Evangelos Simoudis IBM Almaden Research, USA Enquiries ========= General: Xiaohui Liu Department of Computer Science Birkbeck College Malet Street London WC1E 7HX, UK E-mail: hui@dcs.bbk.ac.uk Tel: (+44) 171 631 6711 Fax: (+44) 171 631 6727 Technical Program: Paul Cohen Department of Computer Science University of Massachusetts, Amherst Amherst, MA 01003-4610 USA E-mail: cohen@cs.umass.edu Tel: (+1) 413 545 3638 Fax: (+1) 413 545 1249 Exhibition: Richard Weber MIT GmbH Promenade 9 52076 Aachen Germany E-mail: rw@mitgmbh.de Tel: (+49) 2408 94580 Fax: (+49) 2408 94582 Finance: Sylvie Jami Department of Computer Science Birkbeck College Malet Street London WC1E 7HX, UK E-mail: s.jami@dcs.bbk.ac.uk Tel: (+44) 171 631 6726 Fax: (+44) 171 631 6727 Local Arrangements: Trevor Fenner Department of Computer Science Birkbeck College Malet Street London WC1E 7HX, UK E-mail: hui@dcs.bbk.ac.uk Tel: (+44) 171 631 6704 Fax: (+44) 171 631 6727 Publicity & Michael Berthold Publication: Universitaet Karlsruhe, IRF Am Zirkel 2 76128 Karlsruhe, Germany E-mail: berthold@ira.uka.de Tel: (+49) 721 608 4219 Fax: (+49) 721 370 455 Sponsorship: Mihaela Ulieru Simon Fraser University 2357 Riverside Drive North Vancouver, B.C. Canada V7H 1V8 Email: mhs@robotics.eecs.berkeley.edu Tel: (+1) 604 924 1001 Fax: (+1) 604 924 1006 There is also an IDA-97 mailing list. To subscribe, send the word "subscribe" in the message body to: ida97-request@dcs.bbk.ac.uk Latest information regarding IDA-97 will be available on the World Wide Web Server of the Department of Computer Science at Birkbeck College, London: http://web.dcs.bbk.ac.uk/ida97.html ------------------------------ Date: Tue, 30 Apr 1996 16:34:59 +0800 From: Michael Hadjimichael Subject: CFP: Rough Sets and Soft Computing, 1997 THE FIFTH INTERNATIONAL WORKSHOP ON ROUGH SETS AND SOFT COMPUTING (RSSC'97) Honorary Chair: Zdzislaw Pawlak in ************************************************************ * Third Joint Conference on Information Sciences (JCIS'97) * * HONORARY CONFERENCE CHAIRS * * Lotfi A. Zadeh & Azriel Rosenfeld * ************************************************************ Sheraton Imperial Hotel & Convention Center Research Triangle Park, NC 27709, USA March 1, 1997 (Tutorials) March 2 - 5, 1997 (Conferences) CALL FOR PAPERS Rough sets and fuzzy sets are complementary generalizations of classical sets. Fuzzy sets allow partial set memberships to handle vagueness, while rough sets allow multiple set memberships to deal with indiscernibility. These two approaches to generalized sets form a beginning of a "soft mathematics" and provide a basis for "soft computing", which includes, along with rough sets, at least fuzzy logic, neural networks, probabilistic reasoning, belief networks, learning, connectionist computing, genetic algorithms, and chaos theory. This workshop will allow researchers to exchange their differing views of soft computing and the application of soft mathematics to the handling of uncertainty. This exchange should lead to mutually beneficial co-operation. RSSC'97 (CO-)SPONSORS Amdahl Corproration American Association for Artificial Intelligence IEEE Computer Society, Technical Committee on Microprocessors and Microcomputers International Rough Set Society Internet Research Institute for Rough Set Study Inter. Assoc. for Mathematics and Computers in Simulation San Jose State University ORGANIZATION Program Chair: T. Y. Lin Department of Mathematics and Computer Science San Jose State University San Jose, California 95192, USA e-mail: tylin@sjsumcs.SJSU.EDU, Tel: 408-924-5121 Program Co-Chair: Akira Nakamura Department of Computer Science, Meiji University 1-1-1, Higashi-mita, Tama-ku Kawasaki 214, Japan e-mail: nakamura@cs.meiji.ac.jp, Tel: +81 44 934 7469 Secretary: Mike Hadjimichael, Naval Research Laboratory - Monterey 7 Grace Hopper Ave., Monterey, CA 93940, USA e-mail: hadjimic@nrlmry.navy.mil, Tel: 408-656-6010 Organizing Chair: Anita Wasilewska Department of Computer Science State University of New York, Stony Brook Stony Brook, NY 11794, USA email: anita@cs.sunysb.edu, Tel: 516-632-8458 Finance Chair: E. Hamann Publicity: Y. Y. Yao (Chair), yyao@thunder.lakeheadu.ca A. Lotfi, lotfia@marg.ntu.ac.uk J. Stefanowski, Jerzy.Stefanowski@cs.put.poznan.pl T. Yokomori, yokomori@cs.uec.ac.jp, tyokomori@daisy.uwaterloo.ca STEERING COMMITTEE Z. Pawlak, T.Y. Lin, A. Nakamura, R. Slowinski, W. Ziarko, J. Grzymala-Busse, T. Munakata, Z. Ras, A. Skowron, M. Wong, J. Zytkow SUBMISSION INFORMATION *Hardcopy submissions should be sent to: (Electronic submission is encouraged) T. Y. Lin, Department of Mathematics and Computer Science, San Jose State University, San Jose, California 95192-0103 USA e-mail: tylin@sjsumcs.SJSU.EDU tylin@CALSTATE.BITNET Tel: 408-924-5121 Fax: 408-924-5080 *Electronic submissions (Postscript) should be sent to: M. Hadjimichael NRL-Monterey, 7 Grace Hopper Ave Monterey, CA 93943-5502, USA 408-656-6010 / fax 408-656-4769 EMAIL: hadjimic@nrlmry.navy.mil ******************************************* * IMPORTANT JCIS'97 DEADLINES TO REMEMBER * ******************************************* (1) Deadline for summaries submission: RSSC'97: October 6. 1996 JCIS: December 6, 1996. (2) Proposal for organized sessions: any time up to December 20, 1996. (3) Paper acceptance or rejection: January 1, 1997. (4) Program (Electronic Version): January 1, 1997. (5) Absolute deadline for conference fee deposit: January 15, 1997. (6) Official program available: February 1, 1997. (5) Deadline for full length paper: March 4, 1997. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 5th ANNUAL LOTFI A. ZADEH BEST PAPER AWARD COMPETITION Open to all JCIS'97 attendees, certificate, $2,000 prize and Hotel accommodations attending the next JCIS ****************************************************************************** JCIS'97 Information (excerpts from CFP) ****************************************************************************** TIME SCHEDULE AND VENUE ---------------------------------------------------- | SPONSORS: | | | | Information Science Journals - Sections A, B & C | | | | Elsevier Science Publishing Inc. | | New York, N.Y. | | | | Machine Intelligence and Fuzzy Logic Laboratory | | Duke University | | | ---------------------------------------------------- ******************************************************************************* JCIS'97 REGISTRATION FEES & INFORMATION Up to 1/1/97 After 1/1/97 Full Registration $320.00 $440.00 Student Registration $120.00 $180.00 Tutorial(per Mini-Course) $120.00 $160.00 Exhibit Boot Fee $300.00 $400.00 One Day Fee(no pre-reg. discount) $195.00 $ 95.00 (Student) Above fees applicable to all three conferences & three workshops FULL CONFERENCE REGISTRATION: Includes admission to all sessions, exhibit area, coffee, tea and soda. A copy of conference proceedings (summary) at conference. In addition, the right to purchase the hard-cover deluxe books at 1/2 price, and the proceedings of companion conferences, workshops of JCIS'97, also, at half price. Award Banquet on March 3, 1997 and lunches on March 2, 3 & 4 are also included through Full Registration. One day registration does not include banquet, but it does include one lunch on the day registered. Tutorials are not included. STUDENT CONFERENCE REGISTRATION: ( For full-time students only. A letter from your department is required. You must present a current student ID with picture.) Includes a copy of conference proceedings (summary), admission to all sessions, exhibit area, coffee, tea and soda, the right to purchase the hard-cover deluxe books at 1/2 price, and companion proceedings at 1/2 price. Single student author must pay $150 in addition. TUTORIALS REGISTRATION: Any person can register for the Tutorials. A copy of lecture notes for the course registered is included. Coffee, tea and soda are included. The right to purchase the hard-cover deluxe books and all companion JCIS'97 proceedings are included. PUBLICATIONS The Joint Conferences publishes three or four proceedings on summaries which consists of all papers accepted by all respective program committees. The JCIS Proceedings will be made available on March 1, 1997, for all three conferences & three workshops depending upon the total number of pages for each conference or workshop. A summary shall not exceed 4 pages of 10-point font, double-column, single-spaced text, (1 page minimum) with figures and tables included. Any summary exceeding 4 pages will be charged $50 per additional page. Three copies of the summary are required by Dec. 15, 1996. A deposit of $150 check must be included to guarantee the publication of your 4 pages summary in the Proceedings. The absolute deadline for the deposit is Jan. 15, 1997. For multiple papers author, the following deposit schedule will be observed: one paper, $150; two papers, $200; three papers, $250; etc., with $50 increment thereafter. The $150 deposit (one paper) can be deducted from registration fee later. There is no deduction for student registration. It is very important to mark FT & T'97, or CS & I'97, or CI & N'97, or RSSC'97, or SCS'97, or GA'97 on your manuscript (only one of six can be chosen). The conference will make the choice for you if you forget to do so. Final version of the full length paper must be reviewed for possible publication in one of the three INFORMATION SCIENCE JOURNALS or deluxe professional hard cover books. Several special issues will be published in the journal. The number of the special issues will depend upon the quality of papers submitted, the availability of guest editors, the interest of research community in a particular topic and the budget of the publishers. Four (4) copies of the full length paper shall be prepared according to the ``information for Authors'' appearing at the back cover of Information Sciences, an International Journal (Elsevier Publishing Co.). A full paper shall not exceed 20 pages including figures and tables. All full length papers will be reviewed by experts in their respective fields. All fully registered conference attendees will receive a copy of proceeding (summary) of his/her chosen conference or workshop on March 1, 1997. Lastly, attendees will have the opportunity to purchase any or all of Vol.I, Vol.II and Vol.III of ``Advances in Fuzzy Theory & Technology'' as well as Vol. IV ``Advances in Information Sciences''. These are hard-covered, deluxe, professional books at 1/2 price. ------------------------------ Date: Sat, 4 May 1996 08:20:01 -0700 (PDT) From: "John R. Koza" Subject: GP-96 Registration and Papers CALL FOR PARTICIPATION, LIST OF TUTORIALS, LIST OF PAPERS, LIST OF PROGRAM COMMITTEES, AND REGISTRATION FORM (Largest discount availabe until May 15) Genetic Programming 1996 Conference (GP-96) July 28 - 31 (Sunday - Wednesday), 1996 Fairchild Auditorium and other campus locations Stanford University Stanford, California Proceedings will be published by The MIT Press In cooperation with -the Association for Computing Machinery (ACM), - SIGART - IEEE Neural Network Council, - American Association for Artificial Intelligence. Genetic programming is an automatic programming technique for evolving computer programs that solve (or approximately solve) problems. Starting with a primordial ooze of thousands of randomly created computer programs composed of programmatic ingredients appropriate to the problem, a population of computers programs is progressively evolved over many generations using the Darwinian principle of survival of the fittest, a sexual recombination operation, and occasional mutation. Since 1992, over 500 technical papers have been published in this rapidly growing field. This first genetic programming conference will feature 75 papers and 27 poster papers, 12 tutorials, 2 invited speakers, a session featuring late-breaking papers, and informal birds-of-a-feather meetings. Topics include, but are not limited to, applications of genetic programming, theoretical foundations of genetic programming, implementation issues and technique extensions, use of memory and state, cellular encoding (developmental genetic programming), evolvable hardware, evolvable machine language programs, automated evolution of program architecture, evolution and use of mental models, automatic programming of multi-agent strategies, distributed artificial intelligence, automated circuit synthesis, automatic programming of cellular automata, induction, system identification, control, automated design, compression, image analysis, pattern recognition, molecular biology applications, grammar induction, and parallelization. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ HONORARY CHAIR: John Holland, University of Michigan INVITED SPEAKERS: John Holland, University of Michigan and David E. Goldberg, University of Illinois GENERAL CHAIR: John Koza, Stanford University PUBLICITY CHAIR: Patrick Tufts, Brandeis University ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TUTORIALS -Sunday July 28 9:15 AM - 11:30 AM - Genetic Algorithms - David E. Goldberg, University of Illinois - Machine Language Genetic Programming - Peter Nordin, University of Dortmund, Germany - Genetic Programming using Mathematica P Robert Nachbar P Merck Research Laboratories - Introduction to Genetic Programming - John Koza, Stanford University ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Sunday July 28 1:00 PM - 3: 15 PM - Classifier Systems- Robert Elliott Smith, University of Alabama - Evolutionary Computation for Constraint Optimization - Zbigniew Michalewicz, University of North Carolina - Advanced Genetic Programming - John Koza, Stanford University ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Sunday July 28 3:45 PM - 6 PM - Evolutionary Programming and Evolution Strategies - David Fogel, University of California, San Diego - Cellular Encoding P Frederic Gruau, Stanford University (via videotape) and David Andre, Stanford University (in person) - Genetic Programming with Linear Genomes (one hour) - Wolfgang Banzhaf, University of Dortmund, Germany -JECHO - Terry Jones, Santa Fe Institute ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tuesday July 30 - 3 PM - 5:15PM - Neural Networks - David E. Rumelhart, Stanford University - Machine Learning - Pat Langley, Stanford University -JMolecular Biology for Computer Scientists - Russ B. Altman, Stanford University ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Additional tutorial P Time to be Announced % Evolvable Hardware - Hugo De Garis,ATR, Nara, Japan and Adrian Thompson, University of Sussex, U.K. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FOR MORE INFORMATION ABOUT THE GP-96 CONFERENCE: See the GP-96 home page on the World Wide Web: http://www.cs.brandeis.edu/~zippy/gp-96.html or contact GP-96 at via e-mail at gp@aaai.org. PHONE: 415-328- 3123. FAX: 415-321-4457. Conference operated by Genetic Programming Conferences, Inc. (a California not- for-profit corporation). ABOUT GENETIC PROGRAMMING IN GENERAL: http://www-cs- faculty.stanford.edu/~koza/. FOR GP-96 TRAVEL INFORMATION: See the GP-96 home page on the World Wide Web: http://www.cs.brandeis.edu/~zippy/gp-96.html. For further information regarding special GP-96 airline and car rental rates, please contact Conventions in America at e-mail flycia@balboa.com; or phone 1-800-929-4242; or phone 619-678-3600; or FAX 619-678-3699. FOR HOTEL AND UNIVERSITY HOUSING INFORMATION: See the GP-96 home page on the World Wide Web: http://www.cs.brandeis.edu/~zippy/gp-96.html or via e- mail at gp@aaai.org. FOR STUDENT TRAVEL GRANTS: See the GP-96 home page on the World Wide Web: http://www.cs.brandeis.edu/~zippy/gp-96.html. ABOUT THE SAN FRANCISCO BAY AREA AND SILICON VALLEY SIGHTS: Try the Stanford University home page at http://www.stanford.edu/, the Hyperion Guide at http://www.hyperion.com/ba/sfbay.html; the Palo Alto weekly at http://www.service.com/PAW/home.html; the California Virtual Tourist at http://www.research.digital.com/SRC/virtual- tourist/California.html; and the Yahoo Guide of San Francisco at http://www.yahoo.com/Regional_Information/States/Califor nia/San_Francisco. ABOUT OTHER CONTEMPORANEOUS WEST COAST CONFERENCES: Information about the AAAI-96 conference on August 4 P 8 (Sunday P Thursday), 1996, in Portland, Oregon is at http://www.aaai.org/. Information on the International Conference on Knowledge Discovery and Data Mining (KDD- 96) in Portland on August 3 P 5, 1996 is at http://www- aig.jpl.nasa.gov/kdd96. Information about the Protein Society conference on August 3 P 7, 1996 in San Jose is at http://www.faseb.org. Information about the Foundations of Genetic Algorithms (FOGA) workshop on August 3 P 5 (Saturday P Monday), 1996, in San Diego is at http://www.aic.nrl.navy.mil/galist/foga/. Information about the Parallel and Distributed Processing Techniques and Applications (PDPTA-96) conference on August 6 P 9 (Friday P Sunday), 1996 in Sunnyvale, California is at http://www.ece.neu.edu/pdpta96.html. ABOUT MEMBERSHIP IN THE ACM, AAAI, or IEEE: For information about ACM membership, try http://www.acm.org/; for information about SIGART, try http://sigart.acm.org/; for AAAI membership, go to http://www.aaai.org/; and for membership in the IEEE, go to http://www.ieee.org. PHYSICAL MAIL ADDRESS FOR GP-96: GP-96 Conference, c/o American Association for Artificial Intelligence, 445 Burgess Drive, Menlo Park, CA 94025. PHONE: 415-328- 3123. FAX: 415-321-4457. WWW: http://www.aaai.org/. E-MAIL: gp@aaai.org. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ REGISTRATION FORM FOR GENETIC PROGRAMMING 1996 CONFERENCE TO BE HELD ON JULY 28 P 31, 1996 AT STANFORD UNIVERSITY First Name _________________________ Last Name_______________ Affiliation________________________________ Address__________________________________ ________________________________________ City__________________________ State/Province _________________ Zip/Postal Code____________________ Country__________________ Daytime telephone__________________________ E-Mail address_____________________________ Conference registration fee includes copy of proceedings, attendance at 4 tutorials of your choice, syllabus books for the tutorials, conference reception, copy of a book of late-breaking papers, a T-shirt, coffee breaks, lunch (on at least Sunday), and admission to conference sessions. Students must send legible proof of full-time student status. Conference proceedings will be mailed to registered attendees with U.S. mailing addresses via 2-day U.S. priority mail about 1 P 2 weeks prior to the conference at no extra charge (at addressee's risk). If you are uncertain as to whether you will be at that address at that time or DO NOT WANT YOUR PROCEEDINGS MAILED to you at the above address for any other reason, your copy of the proceedings will be held for you at the conference registration desk if you CHECK HERE ____. Postmarked by May 15, 1996: Student P ACM, IEEE, or AAAI Member $195 Regular P ACM, IEEE, or AAAI Member $395 Student P Non-member $215 Regular P Non-member $415 Postmarked by June 26, 1996: Student P ACM, IEEE, or AAAI Member $245 Regular P ACM, IEEE, or AAAI Member $445 Student P Non-member $265 Regular P Non-member $465 Postmarked later or on-site: Student P ACM, IEEE, or AAAI Member $295 Regular P ACM, IEEE, or AAAI Member $495 Student P Non-member $315 Regular P Non-member $515 Member number: ACM # ___________ IEEE # _________ AAAI # _________ Total fee (enter appropriate amount) $ _________ __ Check or money order made payable to "AAAI" (in U.S. funds) __ Mastercard __ Visa __ American Express Credit card number __________________________________________ Expiration Date ___________ Signature _________________________ TUTORIALS: Check off a box for one tutorial from each of the 4 columns: Sunday July 28, 1996 P 9:15 AM - 11:30 AM __ Genetic Algorithms __ Machine Language GP __ GP using Mathematica __ Introductory GP Sunday July 28, 1996 P 1:00 PM - 3: 15 PM __ Classifier Systems __ EC for Constraint Optimization __ Advanced GP Sunday July 28, 1996 P 3:45 PM - 6 PM __ Evolutionary Programming and Evolution Strategies __ Cellular Encoding __ GP with Linear Genomes __ ECHO Tuesday July 30, 1996 P3:00 PM - 5:15PM __ Neural Networks __ Machine Learning __ Molecular Biology for Computer Scientists __ Check here for information about housing and meal package at Stanford University. __ Check here for information on student travel grants. T-shirt size ___ small ___ medium ___ large ___ extra-large No refunds will be made; however, we will transfer your registration to a person you designate upon notification. SEND TO: GP-96 Conference, c/o American Association for Artificial Intelligence, 445 Burgess Drive, Menlo Park, CA 94025. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 PAPERS APPEARING IN PROCEEDINGS OF THE GP-96 CONFERENCE TO BE HELD AT STANFORD UNIVERSITY ON JULY 28-31, 1996 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ LONG GENETIC PROGRAMMING PAPERS Discovery by Genetic Programming of a Cellular Automata Rule that is Better than any Known Rule for the Majority Classification Problem --- David Andre, Forrest H Bennett III, and John R. Koza A Study in Program Response and the Negative Effects of Introns in Genetic Programming --- David Andre and Astro Teller An Investigation into the Sensitivity of Genetic Programming to the Frequency of Leaf Selection During Subtree Crossover --- Peter J. Angeline Automatic Creation of an Efficient Multi-Agent Architecture Using Genetic Programming with Architecture-Altering Operations --- Forrest H Bennett III Evolving Deterministic Finite Automata Using Cellular Encoding --- Scott Brave Genetic Programming and the Efficient Market Hypothesis --- Shu-Heng Chen and Chia-Hsuan Yeh Bargaining by Artificial Agents in Two Coalition Games: A Study in Genetic Programming for Electronic Commerce --- Garett Dworman, Steven O. Kimbrough, and James D. Laing Waveform Recognition Using Genetic Programming: The Myoelectric Signal Recognition Problem --- Jaime J. Fernandez, Kristin A. Farry, and John B. Cheatham Benchmarking the Generalization Capabilities of A Compiling Genetic programming System using Sparse Data Sets --- Frank D. Francone, Peter Nordin, and Wolfgang Banzhaf A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks --- Frederic Gruau, Darrell Whitley, and Larry Pyeatt Entailment for Specification Refinement --- Thomas Haynes, Rose Gamble, Leslie Knight, and Roger Wainwright Genetic Programming of Near-Minimum-Time Spacecraft Attitude Maneuvers --- Brian Howley Evolving Evolution Programs: Genetic Programming and L-Systems --- Christian Jacob Genetic Programming using Genotype-Phenotype Mapping from Linear Genomes into Linear Phenotypes --- Robert E. Keller and Wolfgang Banzhaf Automated WYWIWYG Design of Both the Topology and Component Values of Electrical Circuits Using Genetic Programming --- John R. Koza, Forrest H Bennett III, David Andre, and Martin A. Keane Use of Automatically Defined Functions and Architecture-Altering Operations in Automated Circuit Synthesis Using Genetic Programming --- John R. Koza, David Andre, Forrest H Bennett III, and Martin A. Keane Using Data Structures within Genetic Programming --- W. B. Langdon Evolving Teamwork and Coordination with Genetic Programming --- Sean Luke and Lee Spector Using Genetic Programming to Develop Inferential Estimation Algorithms --- Ben McKay, Mark Willis, Gary Montague, and Geoffrey W. Barton Dynamics of Genetic Programming and Chaotic Time Series Prediction --- Brian S. Mulloy, Rick L. Riolo, and Robert S. Savit Genetic Programming, the Reflection of Chaos, and the Bootstrap: Towards a useful Test for Chaos --- E. Howard N. Oakley Solving Facility Layout Problems Using Genetic Programming --- Jaime Garces-Perez, Dale A. Schoenefeld, and Roger L. Wainwright Variations in Evolution of Subsumption Architectures Using Genetic Programming: The Wall Following Robot Revisited --- Steven J. Ross, Jason M. Daida, Chau M. Doan, Tommaso F. Bersano- Begey, and Jeffrey J. McClain MASSON: Discovering Commonalties in Collection of Objects using Genetic Programming --- Tae-Wan Ryu and Christoph F. Eick Cultural Transmission of Information in Genetic Programming --- Lee Spector and Sean Luke Code Growth in Genetic Programming --- Terence Soule, James A. Foster, and John Dickinson High-Performance, Parallel, Stack-Based Genetic Programming --- Kilian Stoffel and Lee Spector Search Bias, Language Bias, and Genetic Programming --- P. A. Whigham Learning Recursive Functions from Noisy Examples using Generic Genetic Programming --- Man Leung Wong and Kwong Sak Leung SHORT GENETIC PROGRAMMING PAPERS Classification using Cultural Co-Evolution and Genetic Programming --- Myriam Abramson and Lawrence Hunter Type-Constrained Genetic Programming for Rule-Base Definition in Fuzzy Logic Controllers --- Enrique Alba, Carlos Cotta, and Jose J. Troyo The Evolution of Memory and Mental Models Using Genetic Programming --- Scott Brave Automatic Generation of Object-Oriented Programs Using Genetic Programming --- Wilker Shane Bruce Evolving Event Driven Programs --- Mark Crosbie and Eugene H. Spafford Computer-Assisted Design of Image Classification Algorithms: Dynamic and Static Fitness Evaluations in a Scaffolded Genetic Programming Environment --- Jason M. Daida, Tommaso F. Bersano-Begey, Steven J. Ross, and John F. Vesecky Improved Direct Acyclic Graph Handling and the Combine Operator in Genetic Programming --- Herman Ehrenburg An Adverse Interaction between Crossover and Restricted Tree Depth in Genetic Programming --- Chris Gathercole and Peter Ross The Prediction of the Degree of Exposure to Solvent of Amino Acid Residues via Genetic Programming --- Simon Handle y A New Class of Function Sets for Solving Sequence Problems --- Simon Handley Evolving Edge Detectors with Genetic Programming --- Christopher Harris and Bernard Buxton Toward Simulated Evolution of Machine Language Iteration --- Lorenz Huelsbergen Robustness of Robot Programs Generated by Genetic Programming --- Takuya Ito, Hitoshi Iba, and Masayuki Kimura Signal Path Oriented Approach for Generation of Dynamic Process Models --- Peter Marenbach, Kurt D. Betterhausen, and Stephan Freyer Evolving Control Laws for a Network of Traffic Signals --- David J. Montana and Steven Czerwinski Distributed Genetic Programming: Empirical Study and Analysis --- Tatsuya Niwa and Hitoshi Iba Programmatic Compression of Images and Sound --- Peter Nordin and Wolfgang Banzhaf Investigating the Generality of Automatically Defined Functions --- Una-May O'Reilly Parallel Genetic Programming: An Application to Trading Models Evolution --- Mouloud Oussaidene, Bastien Chopard, Olivier V. Pictet, and Marco Tomassini Genetic Programming for Image Analysis --- Riccardo Poli Evolving Agents --- Adil Qureshi Genetic Programming for Improved Data Mining: An Application to the Biochemistry of Protein Interactions --- M. L. Raymer, W. F. Punch, E. D. Goodman, and L. A. Kuhn Generality Versus Size in Genetic Programming --- Justinian Rosca Genetic Programming in Database Query Optimization --- Michael Stillger and Myra Spiliopoulou Ontogenetic Programming --- Lee Spector and Kilian Stoffel Using Genetic Programming to Approximate Maximum Clique --- Terence Soule, James A. Foster, and John Dickinson Paragen: A Novel Technique for the Autoparallelisation of Sequential Programs using Genetic Programming --- Paul Walsh and Conor Ryan The Benefits of Computing with Introns --- Mark Wineberg and Franz Oppacher GENETIC PROGRAMMING POSTER PAPERS Co-Evolving Classification Programs using Genetic Programming --- Manu Ahluwalia and Terence C. Fogarty Genetic Programming Tools Available on the Web: A First Encounter --- Anthony G. Deakin and Derek F. Yates Speeding up Genetic Programming: A Parallel BSP Implementation --- Dimitris C. Dracopoulos and Simon Kent Easy Inverse Kinematics using Genetic Programming --- Jonathan Gibbs Noisy Wall-Following and Maze Navigation through Genetic Programming --- Andrew Goldfish Genetic Programming for Classification of Brain Tumours from Nuclear Magnetic Resonance Biopsy Spectra --- H. F. Gray, R. J. Maxwell, I. Martinez-Perez, C. Arus, and S. Cerdan GP-COM: A Distributed Component-Based Genetic Programming System in C++ --- Christopher Harris and Bernard Buxton Clique Detection via Genetic Programming --- Thomas Haynes and Dale Schoenefeld Functional Languages on Linear Chromosomes --- Paul Holmes and Peter J. Barclay Improving the Accuracy and Robustness of Genetic Programming through Expression Simplification --- Dale Hooper and Nicholas S. Flann COAST: An Approach to Robustness and Reusability in Genetic Programming --- Naohiro Hondo, Hitoshi Iba, and Yukinori Kakazu Recurrences with Fixed Base Cases in Genetic Programming --- Stefan J. Johansson Evolutionary and Incremental Methods to Solve Hard Learning Problems --- Ibrahim Kuscu Detection of Patterns in Radiographs using ANN Designed and Trained with the Genetic Algorithm --- Alejandro Pazos Julian Dorado and Antonino Santos The Logic-Grammars-Based Genetic Programming System --- Man Leung Wong and Kwong Sak Leung LONG GENETIC ALGORITHMS PAPERS Genetic Algorithms with Analytical Solution --- Erol Gelenbe Silicon Evolution --- Adrian Thompson SHORT GENETIC ALGORITHMS PAPERS On Sensor Evolution in Robotics --- Karthik Balakrishnan and Vasant Honavar Testing Software using Order-Based Genetic Algorithms --- Edward B. Boden and Gilford F. Martino Optimizing Local Area Networks Using Genetic Algorithms --- Andy Choi A Genetic Algorithm for the Construction of Small and Highly Testable OKFDD Circuits --- Rold Drechsler, Bernd Becker, and Nicole Gockel Motion Planning and Design of CAM Mechanisms by Means of a Genetic Algorithm --- Rodolfo Faglia and David Vetturi Evolving Strategies Based on the Nearest Neighbor Rule and a Genetic Algorithm --- Matthias Fuchs Recognition and Reconstruction of Visibility Graphs Using a Genetic Algorithm --- Marshall S. Veach GENETIC ALGORITHMS POSTER PAPERS The Use of Genetic Algorithms in the Optimization of Competitive Neural Networks which Resolve the Stuck Vectors Problem --- Tin Ilakovac, Zeljka Perkovic, and Strahil Ristov An Extraction Method of a Car License Plate using a Distributed Genetic Algorithm --- Dae Wook Kim, Sang Kyoon Kim, and Hang Joon Kim EVOLUTIONARY PROGRAMMING AND EVOLUTION STRATEGIES PAPERS Evolving Fractal Movies --- Peter J. Angeline Preliminary Experiments on Discriminating between Chaotic Signals --- David B. Fogel and Lawrence J. Fogel Discovering Patterns in Spatial Data using Evolutionary Programming --- Adam Ghozeil and David B. Fogel Evolving Reduced Parameter Bilinear Models for Time Series Prediction using Fast Evolutionary Programming --- Sathyanarayan S. Rao and Kumar Chellapilla CLASSIFIER SYSTEMS PAPERS Three-Dimensional Shape Optimization Utilizing a Learning Classifier System --- Robert A. Richards and Sheri D. Sheppard Classifier System Renaissance: New Analogies, New Directions --- H. Brown Cribbs III and Robert E. Smith Natural Niching for Cooperative Learning in Classifier Systems --- Jeffrey Horn and David E. Goldberg ------------------------------ Date: Wed, 01 May 1996 11:53:14 +0100 From: frisch@minster.cs.york.ac.uk Subject: Research Students Wanted DEPARTMENT OF COMPUTER SCIENCE UNIVERSITY OF YORK INTELLIGENT SYSTEMS GROUP OPPORTUNITIES FOR POSTGRADUATE STUDY IN ARTIFICIAL INTELLIGENCE The Intelligent Systems Group in the Department of Computer Science at the University of York would like to hear from exceptional candidates interested in pursuing a postgraduate research degree (MSc, MPhil, PhD) in areas related to the Group's research interests as outlined on the following pages. The Department has a number of EPSRC-funded fellowships for doctoral candidates and another fellowship that, unlike EPSRC fellowships, provides a stipend to nationals of any EC country. The Department of Computer Science at the University of York provides an outstanding environment for research and postgraduate study. The Department is one of the few computer science departments in the UK whose research has been awarded the top rating of "5" in the most recent Research Assessment Exercise and whose teaching has been awarded the top rating of "excellent" in the HEFCE Teaching Quality Assessment. Based on its evaluation of the Department's research programme, the EPSRC has increased the Department's allocation of research studentships over the past few years, while nationally the total number of studentships has declined. The Department's doctoral program has maintained an extremely high graduation rate: in recent years almost all EPSRC-supported students have submitted a thesis within four years and earned a doctoral degree. Further information on the Group, as well as the Department, can be be accessed on the World Wide Web via URL http://dcpu1.cs.york.ac.uk:9876/isg/home.html Those wishing to discuss opportunities for postgraduate studies within the Intelligent Systems Group should contact either Alan Frisch (frisch@minster.york.ac.uk, +44 1904 432745), Derek Bridge (dgb@minster.york.ac.uk) or Suresh Manandhar (suresh@minster.york.ac.uk) by email or at the Department of Computer Science, University of York, York YO1 5DD, UK. General enquiries about the postgraduate programmes of the Department of Computer Science should be made to Maggie Burton (maggie@minster.york.ac.uk) by email or at the above postal address. DEPARTMENT OF COMPUTER SCIENCE UNIVERSITY OF YORK INTELLIGENT SYSTEMS GROUP The research of the Intelligent Systems Group is concerned with the theoretical principles of artificial intelligence and their application to real-world domains. The Group's research focuses on three core areas of artificial intelligence--knowledge representation and reasoning, machine learning and natural language processing--though most of the Group's projects span these areas. KNOWLEDGE REPRESENTATION AND REASONING is the area of study concerned with determining what knowledge a system requires to produce a certain behaviour, how this knowledge can be encoded and structured for rapid access, and how a system can reason with what it knows. We have developed a framework for enhancing general-purpose deductive systems by embedding into them powerful, special purpose constraint-solving methods. Using this framework, we have developed and studied reasoning systems for knowledge retrieval, constraint logic programming, modal logic deduction, parsing feature-based grammars, inductive learning and planning. In addition to furthering this research, we are investigating constraint-solving algorithms. MACHINE LEARNING is the area of study concerned with how a computational system can acquire knowledge by learning from its experiences and observations. Intuition tells us that a system can learn by generalising what it knows or observes. We have been studying this intuition and its computational consequences in a mathematically rigorous manner. We have formalised the notion of generalisation, studied algorithms for computing generalisations, and identified conditions under which generalisation is an effective mechanism for learning. A major challenge of artificial intelligence is the construction of systems that can find efficient plans of action for accomplishing given tasks. We are developing, and studying the complexity of, algorithms that learn to plan efficiently from examples of optimal plans. Case-based reasoning (CBR) systems solve new problems by analogy to past problems. The theoretical framework we are developing answers questions such as whether the accuracy of these systems necessarily improves as more problems are encountered. We are also developing novel CBR architectures and applying CBR to a number of real domains. NATURAL LANGUAGE PROCESSING research investigates computational methods for understanding and generating human language and has important applications in document processing and user interfaces. We are developing languages for stating the morphological, syntactic and semantic constraints central to modern grammatical theories. We are also developing efficient algorithms for reasoning with these constraints. By combining our work in natural language processing with our expertise in machine learning we are developing methods for learning large-coverage grammars (semi-)automatically from large collections of text. We have already shown how inductive and deductive learning techniques can be combined to give a system that can learn parts of a high quality, wide-coverage natural language grammar. RESEARCH ACTIVITIES The members of the Intelligent Systems Group have been highly active, supervising the completion of six PhD students--all of whom now hold university positions--patenting an architecture for generating navigation directions in natural language, and currently producing their third book. The group has attracted research grants for four projects, one studying methods for representing and reasoning about changing requirements, one studying distributed architectures for case-based reasoning, and two studying applications of case-based reasoning. The ISG maintains close contacts with leading researchers and research groups, both nationally and internationally. During the past three years the group hosted approximately 25 visiting speakers from the UK, US, Canada, Germany, Australia and the Netherlands. The ISG is a member of ESPRIT's COMPULOG NET, the Network of Excellence in Computational Logic. The group co-sponsored AISB's First Workshop on Automated Reasoning and hosted the Fourth European Workshop on Logics in Artificial Intelligence. The ISG has particularly good links with the nearby Division of Artificial Intelligence at the University of Leeds. In addition to conducting collaborative research, the two groups co-sponsor a number of events including the Annual Knowledge Representation and Reasoning Distinguished Lecturer, inviting a leading international AI researcher to visit and speak at the two universities. At York, the ISG collaborates with researchers in the Dept. of Linguistics and in other groups in the Dept. of Computer Science, including the High-Integrity Systems Engineering Group, the Human Computer Interaction Group, and the Advanced Computer Architectures Group. ACADEMIC AND RESEARCH STAFF Derek Bridge, Lecturer. (dgb@minster.york.ac.uk) Natural language processing, case-based reasoning. David Duffy, Research Associate. (dad@minster.york.ac.uk) Automated reasoning and requirements analysis, proof by induction. Alan Frisch, Reader in Intelligent Systems. (frisch@minster.york.ac.uk) Automated reasoning, constraint solving, constraint logic programming, knowledge representation. Suresh Manandhar, Lecturer. (suresh@minster.york.ac.uk) Natural language processing, constraint programming, knowledge representation. Hugh Osborne, Research Associate. (hugh@minster.york.ac.uk) Novel applications of formal methods, especially to case-based reasoning. FURTHER INFORMATION Further information and research papers can be accessed on the World Wide Web at URL http://dcpu1.cs.york.ac.uk:9876/isg/home.html. To discuss educational and research opportunities contact Alan Frisch (phone: +44 1904 432745) or any members of the group at either the email address listed above or at The Department of Computer Science, University of York, Heslington, York YO1 5DD, United Kingdom. DEPARTMENT OF COMPUTER SCIENCE UNIVERSITY OF YORK INTELLIGENT SYSTEMS GROUP ONGOING RESEARCH PROJECTS This document provides brief descriptions of research projects that are representative of those conducted within the Intelligent Systems Group. For convenience the document is divided into three sections--knowledge representation and reasoning, machine learning, and natural language processing--although there is significant overlap among these. KNOWLEDGE REPRESENTATION AND REASONING DEDUCTION WITH CONSTRAINTS Alan Frisch One of the most widely-used and successful approaches to increasing the efficiency of general-purpose automated reasoning systems has been that of integrating special-purpose reasoning systems into them, resulting in what are often called hybrid reasoning systems. Though the resulting hybrid reasoning systems are appealing, their construction and analysis can be difficult. Our research helps to remedy this problem for a particular class of hybrid reasoners that we have identified and dubbed ``substitutional reasoners''. Substitutional reasoners share certain architectural features; most notably they (1) operate on a language that contains a distinguished set of symbols for representing constraints on the values over which quantified variables range, and (2) employ a special purpose reasoning system to test the satisfiability of these constraints. One of the distinguishing features of substitutional reasoners is that the constraints are manipulated exclusively by the special-purpose reasoner. Though the substitutional architecture has been one of the most common and successful architectures for hybrid reasoning, our research is the first to identify these reasoners as a single class and to investigate their common properties and the general principles that underly them. Our results support a framework that enables the systematic production of substitutional reasoners and their completeness proofs from certain kinds of non-hybrid reasoners and their completeness proofs. Within the substitutional framework we have studied reasoning systems for knowledge retrieval, constraint logic programming, modal logic deduction, parsing feature-based grammars, inductive learning with background information and planning in temporally rich domains. CONSTRAINT SOLVING Alan Frisch In contrast to our results on deduction with constraints, which have been obtained by abstracting away from algorithmic issues and concentrating on architectural issues, we are taking a growing interest in constraint-solving algorithms. Our previous work has studied sorted unification, an operation that lies at the heart of all automated deduction systems for sorted logic, and which can be seen as jointly solving membership and equational constraints. Our current work studies the relationship of deduction to the problem of simultaneously satisfying a set of symbolic constraints on finite domains. Future efforts will concentrate on integrating deductive methods and traditional constraint satisfaction techniques to effectively solve large constraint satisfaction problems. REASONING ABOUT CHANGING REQUIREMENTS David Duffy This project is concerned with the representation of requirements and design decisions, and the rationale associated with them, in a way that is amenable to automated reasoning. The goal is to develop a methodology both for reasoning about the implications (and hence costs) of changes to requirements, and for assessing the opportunities for changes in order to adapt and improve system designs. Early work concentrated on the development of a goal-based framework for combining informal and formal representations of requirements and ensuring their integrity. Subsequently, we have focused on the problems of extracting formal descriptions from requirements expressed using controlled natural languages, and the use of proof mechanisms for assessing the sensitivity of requirements to change. This work forms part of a broader project (in conjunction with the High Integrity Systems Group at York, with Newcastle and Loughborough Universities and with a number of industrial partners) on processes for dealing with changing requirements, which is now coming to completion. KNOWLEDGE-BASED SYSTEMS DESIGN Derek Bridge, Hugh Osborne Our early work included the use of object-orientation to structure logic databases, but more recently all our work has taken on a case-based reasoning (CBR) flavour. A short project with BT Plc investigated how the services provided by Help Desks could be improved by the use of knowledge based techniques. We built a small prototype system which used CBR to assist a Help Desk Operator carry out a partial diagnosis of a customer's problem. Subsequent work, carried out in the Human-Computer Interaction Group undertook the formal specification, using Z, of a variety of properties of case-based systems. These specifications gave insight into the `space' of possible case-based systems, and elucidated human interaction properties. Finally, in collaboration with the Advanced Architectures Group, we are working on a project entitled `Architectures for Heterogeneous Knowledge Manipulation Systems', which is part of the EPSRC-funded special research programme Architectures for Knowledge Manipulation Systems. The knowledge-based systems side of this project will characterise functional properties of stand alone CBR systems and the circumstances under which these properties are preserved in integrated systems and in distributed environments. The properties will be characterised both formally and empirically. So far we have devised a rich set of human-interpretable similarity measures and derived normal forms for these that allow their parallel evaluation. Industrial support for the project comes in the form of a PARAMID multi-processor from Transtech Ltd., and the supply of example data from a U.K. bank. In the future, we intend to continue to blend both formal and empirical methods in our research in this area. MACHINE LEARNING LEARNING TO PLAN AND ACT Derek Bridge, Robert Dormer, Klaas Schilstra Planning has traditionally been treated within the artificial intelligence community with a focus on search: finding a sequence of operators which will transform an initial state into a goal state. For complex systems, however, the computational cost of this approach is prohibitive. Humans on the other hand are able to plan in complex environments, by using skills and techniques learned from analogous situations that have been encountered previously. The aim of this work is to investigate the use of learning techniques, such as inductive logic programming, for improving the efficiency of logic-based planners. We are also looking at the use of statistical learning theories (such as PAC learning) to obtain bounds on problem complexity. More recently, we have turned to case-based reasoning and learning as a way of furnishing planners with knowledge of plan execution experience that can be used to build more robust plans. CASE-BASED LEARNING Derek Bridge, Tony Griffiths Using the PAC-learning model of machine learning, we are attempting to answer questions such as whether the performance of a case-based reasoning system necessarily improves as more cases are added to the case base. In particular, we have formalised the knowledge content of case-based systems, shown that they often have concept spaces that are different from their hypothesis spaces, and shown how the similarity measure encodes learning bias. More recently we have described two algorithms whose average-case learning behaviours (which we have been able to characterise precisely) we propose should act as yardsticks against which the observed performance of case-based learners can be measured. INDUCTIVE CONSTRAINT LOGIC PROGRAMMING Alan Frisch, Simon Anthony Inductive Logic Programming (ILP) is concerned with learning logic programs from sets of examples and, often, some background knowledge. Though ILP systems have been applied with great success to a number of real-world problems, they inherit some of the shortcomings inherent in the traditional logic programming paradigm. In particular, with traditional logic programming languages it is difficult to naturally express computations over domains other than the Herbrand universe (the set of variable-free logical terms). Thus logic programming languages usually require extra-logical constructions to express operations such as arithmetic ones. Consequently, the major results of ILP, which are formulated for pure logic programs, cannot be applied directly to non-Herbrand domains. Constraint logic programming generalises the ideas of ordinary logic programming to allow computation over non-Herbrand domains in a principled and natural manner. This is achieved by replacing the unification procedure of ordinary logic programming with more general constraint-solving mechanisms. Our research is attempting to take the the major ideas and results from ILP and generalise them to the learning of constraint logic programs. Our goal is to demonstrate that the resulting enterprise--Inductive Constraint Logic Programming--provides useful methods for learning in non-Herbrand domains such as numerical domains. NATURAL LANGUAGE PROCESSING CONSTRAINT LOGICS FOR NATURAL LANGUAGE PROCESSING Suresh Manandhar, Alan Frisch Ambiguity arises at all levels of linguistic knowledge--morphology, phonology, syntax, semantics and discourse. A natural language processing system incurs heavy penalties if its implementation does not employ a representation that is largely non-committal. Our recent work has focussed on the use of underspecified representations to represent and reason efficiently with ambiguities. We have developed constraint logics that provide logically sound and efficient mechanisms to represent and reason with such underspecified structures. Our future work will concentrate on formulating a general purpose constraint-solving scheme suitable for specifying complex constraint-based grammars for use in a generic parsing and generation architecture. We will also attempt to develop a hybrid constraint logic that combines constraint reasoning with probabilistic information. Such a logic could be used to obtain the most probable interpretation of a highly ambiguous representation. Our goal is to specify and implement a future proof formalism that subsumes current constraint-based formalisms by allowing development of large hybrid constraint-based grammars. MACHINE LEARNING OF CONSTRAINT-BASED GRAMMARS Suresh Manandhar, Derek Bridge Modern constraint-based grammatical theories, such as Head-driven Phrase Structure Grammar (HPSG), employ a complex range of constraints for representing linguistic knowledge. On the one hand, such a rich grammatical theory makes it possible to write grammars that contain very rich linguistic knowledge. On the other hand, it is not entirely clear how constraint-based grammars can be learned (semi-)automatically from large corpora. This means that there is a need to study the complexity/learnability divide and come up with a refined but equally expressive grammatical theory that has the advantage of being acquired automatically from corpora. Our efforts so far have been devoted towards combining deductive and inductive techniques for learning unification grammars in the style of Generalised Phrase-Structure Grammar. This approach was successful in learning grammars that reduced overgeneration and undergeneration, and which assigned linguistically plausible analyses to sentences. Future work will build on our past work and other existing work in corpus linguistics, constraint-based grammars, knowledge representation and machine learning with a view to learning HPSG-style unification grammars. ------------------------------ End of ML-LIST (Digest format) **************************************** From jdcohen+@andrew.cmu.edu Tue May 14 16:24:26 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id QAA20484 for ; Tue, 14 May 1996 16:24:20 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id QAA28913 for ; Tue, 14 May 1996 16:24:18 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab20893; 14 May 96 15:24:32 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa20885; 14 May 96 14:59:17 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa28751; 14 May 96 14:58:31 EDT Message-ID: Date: Tue, 14 May 1996 14:21:39 -0400 (EDT) From: "Jonathan D. Cohen" To: Connectionists@cs.cmu.edu Subject: Postdoc Position Available Postdoctoral Position: Computational Modeling of Neuromodulation and/or Prefrontal Cortex Function ---------------- Center for the Neural Basis of Cognition Carnegie Mellon University and the University of Pittsburgh ---------------- A postdocotral position is available starting September 1, 1996 for someone interested in pursuing computational modeling approaches to the role of neuromodulation and/or prefrontal cortical function in cognition. The nature of the position is flexible, depending upon the individual's interest and expertise. Approaches can be focused at the neurobiological level (e.g., modeling detailed physiological characteristics of neuromodulatory systems, such as locus coeruleus and/or dopaminergic nuclei, or the circuitry of prefrontal cortex), or at the more cognitive level (e.g., the nature of representations and/or the mechanisms involved in active maintenance of information within prefrontal cortex, and their role in working memory). The primary requirement for the position is a Ph.D. in the cognitive, computational, or neurosciences, and extensive experience with computational modeling work, either at the PDP/connectionist or detailed biophysical level. The candidate will be working directly with Jonathan Cohen and Randall O'Reilly within the Department of Psychology at CMU, and in potential collaboration with other members of the Center for the Neural Basis of Cognition (CNBC), including James McClelland, David Lewis, German Barrionuevo, Susan Sesack, G. Bard Ermantrout, as well as collaborators at other institutions, such as Gary Aston-Jones (Hahnemann University), Joseph LeDoux (NYU) and Peter Dayan (MIT). Available resources include direct access to state-of-the-art computing facilities within the CNBC (IBM SP-2 and SGI PowerChallenge), neuroimaging facilities (PET and 3T fMRI at the University of Pittsburgh), and clinical populations (Western Psychiatric Institute and Clinic). Carnegie Mellon University and the University of Pittsburgh are both equal opportunity employers; minorities and women are encouraged to apply. Inquiries can be directed to Jonathan Cohen (jdcohen@cmu.edu) or Randy O'Reilly (oreilly@cmu.edu). Applicants should send a CV, a small number of relevant publications, and the names and addresses of at least two references, to: Jonathan D. Cohen Department of Psychology Carnegie Mellon University Pittsburgh, PA 15213 (412) 268-2810 From goldfarb@unb.ca Tue May 14 16:24:57 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id QAA20482 for ; Tue, 14 May 1996 16:24:18 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id QAA28911 for ; Tue, 14 May 1996 16:24:16 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa20893; 14 May 96 15:23:53 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa20883; 14 May 96 14:58:25 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa28742; 14 May 96 14:57:21 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa18633; 14 May 96 13:17:10 EDT Received: from hermes.csd.unb.ca by RI.CMU.EDU id aa04069; 14 May 96 13:16:28 EDT Received: (from goldfarb@jupiter.sun.csd.unb.ca [131.202.3.10]) by unb.ca (8.7.5/960430-08:40) id OAA23667; Tue, 14 May 1996 14:06:56 -0300 (ADT) Received: from localhost by jupiter.sun.csd.unb.ca (8.7.4/950215-16:05) id OAA07603; Tue, 14 May 1996 14:06:41 -0300 (ADT) Date: Tue, 14 May 1996 14:06:41 -0300 (ADT) From: Lev Goldfarb X-Sender: goldfarb@jupiter.sun.csd.unb.ca Reply-To: Lev Goldfarb To: inductive@unb.ca, colt@cs.uiuc.edu, ml@ics.uci.edu, connectionists@cs.cmu.edu, cogpsy@neuro.psy.soton.ac.uk, comp-neuro@smaug.bbb.caltech.edu, echos@dmi.ens.fr, NEURO1-L@UICVM.CC.UIC.EDU, alife@cognet.ucla.edu, spp@umiacs.umd.edu, Vision-List@TELEOS.COM, cogni-info@univ-lyon1.fr, neuropl@plearn.edu.pl, neuron-request@CATELL20.psych.upenn.edu, philos-l@liverpool.ac.uk, neur-sci@dl.ac.uk, enns-list@dcs.kcl.ac.uk cc: Lev Goldfarb CS Subject: Workshop: WHAT IS INDUCTIVE LEARNING? (program) Message-ID: MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII Please post. My apologies if you receive multiple copies of the following announcement. ********************************************************************** WHAT IS INDUCTIVE LEARNING? On the foundations of AI and Cognitive Science May 20-21, 1996 held in conjunction with the 11th biennial Canadian AI conference, at the Holiday Inn on King, in Toronto, Canada. Workshop Chair: Lev Goldfarb Each talk (except opening remarks) is 30 min. followed by 30 min. question/discussion period. Monday, May 20, Morning Session ------------------------------- 8:45-9:00 Lev Goldfarb, University of New Brunswick, Canada "Opening Remarks: The inductive learning process as the central cognitive process" 9:00 Chris Thornton, University of Sussex, UK "Does Induction always lead to representation?" 10:10 Lev Goldfarb, University of New Brunswick, Canada "What is inductive learning? Construction of the inductive class representation" 11:20 Anselm Blumer, Tufts University, USA (invited talk) "PAC learning and the Vapnik-Chervonenkis dimension" Monday, May 20, Afternoon Session --------------------------------- 2:00 Charles Ling, University of Western Ontario, Canada (invited talk) "Symbolic and neural network learning in cognitive modeling: Where's the beef?" 3:10 Eduardo Perez, Ricardo Vilalta and Larry Rendell, University of Illinois, USA (invited talk) "On the importance of change of representation in induction" 4:20 Sayan Bhattacharyya and John Laird, University of Michigan, USA "A cognitive model of recall motivated by inductive learning" Tuesday, May 21, Morning Session -------------------------------- 9:00 Ryszard Michalski, George Mason University, USA (invited talk) "Inductive inference from the viewpoint of inferential theory of learning" 10:10 Lev Goldfarb, Sanjay Deshpande and Virendra Bhavsar, University of New Brunswick, Canada "Inductive theory of vision" 11:20 David Gadishev and David Chiu, University of Guelph, Canada "Learning basic elements for texture representation and comparison" Tuesday, May 21, Afternoon Session ---------------------------------- 2:00 John Caulfield, Center of Applied Optics, A&M University, USA (invited talk) "Induction and Physics" 3:10 Igor Jurisica, University of Toronto, Canada "Inductive learning and case-based reasoning" 4:20 Concluding discussion: What is inductive learning? ************************************************************************ URL for Canadian AI'96 Conference http://ai.iit.nrc.ca/cscsi/conferences/ai96.html From icsc@freenet.edmonton.ab.ca Tue May 14 21:16:31 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id VAA24984 for ; Tue, 14 May 1996 21:16:25 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id VAA02957 for ; Tue, 14 May 1996 21:16:23 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa20881; 14 May 96 15:13:59 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa20879; 14 May 96 14:57:18 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa28736; 14 May 96 14:56:50 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa18015; 14 May 96 12:28:07 EDT Received: from fn1.freenet.edmonton.ab.ca by CS.CMU.EDU id aa20502; 14 May 96 12:26:20 EDT Received: by fn1.freenet.edmonton.ab.ca (AIX 3.2/UCB 5.64/4.03) id AA23781; Tue, 14 May 1996 10:25:25 -0600 Date: Tue, 14 May 1996 10:25:24 -0600 (MDT) From: icsc@freenet.edmonton.ab.ca To: Connectionist Mailing List Subject: ISFL'97 Submissions Message-Id: Mime-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII Please note that the deadline for submissions to ISFL'97 approaches on May 31, 1996. Please notify if you need an extension. Announcement and Call for Papers Second International ICSC Symposium on FUZZY LOGIC AND APPLICATIONS ISFL'97 To be held at the Swiss Federal Institute of Technology (ETH), Zurich, Switzerland February 12 - 14, 1997 I. SPONSORS Swiss Federal Institute of Technology (ETH), Zurich, Switzerland and ICSC, International Computer Science Conventions, Canada/Switzerland II. PURPOSE OF THE CONFERENCE This conference is the successor of the highly successful meeting held in Zurich in 1995 (ISFL'95) and is intended to provide a forum for the discussion of new developments in fuzzy logic and its applications. An invitation to participate is extended both to those who took part in ISFL'95 and to others working in this field. Applications of fuzzy logic have played a significant role in industry, notably in the field of process and plant control, especially in applications where accurate modelling is difficult. The organisers hope that contributions will come not only from this field, but also from newer applications areas, perhaps in business, financial planning management, damage assessment, security, and so on. III. TOPICS Contributions are sought in areas based on the list below, which is indicative only. Contributions from new application areas will be particularly welcome. - Basic concepts such as various kinds of Fuzzy Sets, Fuzzy Relations, Possibility Theory - Neuro-Fuzzy Systems and Learning - Fuzzy Decision Analysis - Image Analysis with Fuzzy Techniques - Mathematical Aspects such as non-classical logics, Category Theory, Algebra, Topology, Chaos Theory - Modeling, Identification, Control - Robotics - Fuzzy Reasoning, Methodology and Applications, for example in Artificial Intelligence, Expert Systems, Image Processing and Pattern Recognition, Cluster Analysis, Game Theory, Mathematical Programming, Neural Networks, Genetic Algorithms and Evolutionary Computing - Implementation, for example in Engineering, Process Control, Production, Medicine - Design - Damage Assessment - Security - Business, Finance, Management IV. INTERNATIONAL SCIENTIFIC COMMITTEE (ISC) - Honorary Chairman: M. Mansour, Swiss Federal Institute of Technology, Zurich - Chairman: N. Steele, Coventry University, U.K. - Vice-Chairman: E. Badreddin, Swiss Federal Institute of Technology, Zurich - Members: E. Alpaydin, Turkey P.G. Anderson, USA Z. Bien, Korea H.H. Bothe, Germany G. Dray, France R. Felix, Germany J. Godjevac, Switzerland H. Hellendoorn, Germany M. Heiss, Austria K. Iwata, Japan M. Jamshidi, USA E.P. Klement, Austria B. Kosko, USA R. Kruse, Germany F. Masulli, Italy S. Nahavandi, New Zealand C.C. Nguyen, USA V. Novak, Czech Republic R. Palm, Germany D.W. Pearson, France I. Perfilieva, Russia B. Reusch, Germany G.D. Smith, U.K. V. ORGANISING COMMITTEE ISFL'97 is a joint operation between the Swiss Federal Institute of Technology (ETH), Zurich and International Computer Science Conventions (ICSC), Canada/Switzerland. VI. PUBLICATION OF PAPERS All accepted papers will appear in the conference proceedings, published by ICSC Academic Press. In addition, some selected papers may also be considered for journal publication. VII. SUBMISSION OF MANUSCRIPTS Prospective authors are requested to send two copies of their abstracts of 500 words for review by the International Scientific Committee. All abstracts must be written in English, starting with a succinct statement of the problem, the results achieved, their significance and a comparison with previous work. If authors believe that more details are necessary to substantiate the main claims of the paper, they may include a clearly marked appendix that will be read at the discretion of the International Scientific Committee. The abstract should also include: - Title of proposed paper - Authors names, affiliations, addresses - Name of author to contact for correspondence - E-mail address and fax number of contact author - Name of topic which best describes the paper (max. 5 keywords) Contributions are welcome from those working in industry and having experience in the topics of this conference as well as from academics. The conference language is English. Abstracts may be submitted either by electronic mail (ASCII text), fax or mail (2 copies) to either one of the following addresses: ICSC Canada P.O. Box 279 Millet, Alberta T0C 1Z0 Canada Fax: +1-403-387-4329 Email: icsc@freenet.edmonton.ab.ca or ICSC Switzerland P.O. Box 657 CH-8055 Zurich Switzerland VIII. OTHER CONTRIBUTIONS Anyone wishing to organise a workshop, tutorial or discussion, is requested to contact the chairman of the conference, Prof. Nigel Steele (e-mail: nsteele@coventry.ac.uk / phone: +44-1203-838568 / fax: +44-1203-838585) before August 31, 1996. IX. DEADLINES AND REGISTRATION It is the intention of the organisers to have the conference proceedings available for the delegates. Consequently, the deadlines below are to be strictly respected: - Submission of Abstracts: May 31, 1996 - Notification of Acceptance: August 31, 1996 - Delivery of full papers: October 31, 1996 X. ACCOMMODATION Block reservations will be made at nearby hotels and accommodation at reasonable rates (not included in the registration fee) will be available upon registration (full details will follow with the letters of acceptance) XI. SOCIAL AND TOURIST ACTIVITIES A social programme, including a reception, will be organized on the evening of February 13, 1997. This acitivity will also be available for accompanying persons. Winter is an attractive season in Switzerland and many famous alpine resorts are in easy reach by rail, bus or car for a one or two day excursion. The city of Zurich itself is the proud home of many art galleries, museums or theatres. Furthermore, the world famous shopping street 'Bahnhofstrasse' or the old part of the town with its many bistros, bars and restaurants are always worth a visit. XII. INFORMATION For further information please contact either of the following: - ICSC Canada, P.O. Box 279, Millet, Alberta T0C 1Z0, Canada E-mail: icsc@freenet.edmonton.ab.ca Fax: +1-403-387-4329 Phone: +1-403-387-3546 - ICSC Switzerland, P.O. Box 657, CH-8055 Zurich, Switzerland Fax: +41-1-761-9627 - Prof. Nigel Steele, Chairman ISFL'97, Coventry University, U.K. E-mail: nsteele@coventry.ac.uk Fax: +44-1203-838585 Phone: +44-1203-838568 From isis@cs.monash.edu.au Wed May 15 19:15:02 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id TAA18223 for ; Wed, 15 May 1996 19:14:46 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id TAA21209 for ; Wed, 15 May 1996 19:14:44 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa22441; 15 May 96 17:34:35 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa22439; 15 May 96 17:19:59 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa29724; 15 May 96 17:19:48 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa02844; 15 May 96 5:50:40 EDT Received: from [130.194.64.3] by CS.CMU.EDU id aa27899; 15 May 96 5:49:50 EDT Received: (from isis@localhost) by molly.cs.monash.edu.au (8.7.1/8.6.9) id TAA22314 for Connectionists@cs.cmu.edu; Wed, 15 May 1996 19:49:04 +1000 Date: Wed, 15 May 1996 19:49:04 +1000 From: ISIS conference Message-Id: <199605150949.TAA22314@molly.cs.monash.edu.au> To: Connectionists@cs.cmu.edu Subject: Call for Participation for ISIS ISIS CONFERENCE: INFORMATION, STATISTICS AND INDUCTION IN SCIENCE *** Call for Participation *** Old Melbourne Hotel Melbourne, Australia 20-23 August 1996 INVITED SPEAKERS: Henry Kyburg, Jr. (University of Rochester, NY) Marvin Minsky (MIT) J. Ross Quinlan (Sydney University) Jorma J. Rissanen (IBM Almaden Research, San Jose, California) Ray Solomonoff (Oxbridge Research, Mass) This conference will explore the use of computational modeling to understand and emulate inductive processes in science. The problems involved in building and using such computer models reflect methodological and foundational concerns common to a variety of academic disciplines, especially statistics, artificial intelligence (AI) and the philosophy of science. This conference aims to bring together researchers from these and related fields to present new computational technologies for supporting or analysing scientific inference and to engage in collegial debate over the merits and difficulties underlying the various approaches to automating inductive and statistical inference. About the invited speakers: Henry Kyburg is noted for his invention of the lottery paradox (in "Probability and the Logic of Rational Belief", 1961) and his research since then in providing a non-Bayesian foundation for a probabilistic epistemology. Marvin Minsky is one of the founders of the field of artificial intelligence. He is the inventor of the use of frames in knowledge representation, stimulus for much of the concern with nonmonotonic reasoning in AI, noted debunker of Perceptrons and recently the developer of the "society of minds" approach to cognitive science. J. Ross Quinlan is the inventor of the information-theoretic approach to classification learning in ID3 and C4.5, which have become world-wide standards in testing machine learning algorithms. Jorma J. Rissanen invented the Minimum Description Length (MDL) method of inference in 1978, which has subsequently been widely adopted in algorithms supporting machine learning. Ray Solomonoff developed the notion of algorithmic complexity in 1960, and his work was influential in shaping the Minimum Message Length (MML) work of Chris Wallace (1968) and the Minimum Description Length (MDL) work of Jorma Rissanen (1978). ========================= Tutorials (Tue 20 Aug 96) ========================= 10am - 1pm: Tutorial 1: Peter Spirtes "Automated Learning of Bayesian Networks" Tutorial 2: Michael Pazzani "Machine Learning and Intelligent Info Access" 2pm - 5pm: Tutorial 3: Jan Zytkow "Automation of Scientific Discovery" Tutorial 4: Paul Vitanyi "Kolmogorov Complexity & Applications" About the tutorial leaders: Peter Spirtes is a co-author of the TETRAD algorithm for the induction of causal models from sample data and is an active member of the research group on causality and induction at Carnegie Mellon University. Mike Pazzani is one of the leading researchers world-wide in machine learning and the founder of the UC Irvine machine learning archive. Current interests include the use of intelligent agents to support information filtering over the Internet. Jan Zytkow is one of the co-authors (with Simon, Langley and Bradshaw) of "Scientific Discovery" (1987), reporting on the series of BACON programs for automating the learning of quantitative scientific laws. Paul Vitanyi is co-author (with Ming Li) of "An Introduction to Kolmogorov Complexity and its Applications (1993) and of much related work on complexity and information-theoretic methods of induction. Professor Vitanyi will be visiting the Department of Computer Science, Monash, for several weeks after the conference. A limited number of free student conference registrations or tutorial registrations will be available by application to the organizers in exchange for part-time work during the conference. Program Committee: Hirotugu Akaike, Lloyd Allison, Shun-Ichi Amari, Mark Bedau, Jim Bezdek, Hamparsum Bozdogan, Wray Buntine, Peter Cheeseman, Honghua Dai, David Dowe, Usama Fayyad, Doug Fisher, Alex Gammerman, Clark Glymour, Randy Goebel, Josef Gruska, David Hand, Bill Harper, David Heckerman, Colin Howson, Lawrence Hunter, Frank Jackson, Max King, Kevin Korb, Henry Kyburg, Rick Lathrop, Ming Li, Nozomu Matsubara, Aleksandar Milosavljevic, Richard Neapolitan, Jon Oliver, Michael Pazzani, J. Ross Quinlan, Glenn Shafer, Peter Slezak, Padhraic Smyth, Ray Solomonoff, Paul Thagard, Neil Thomason, Raul Valdes-Perez, Tim van Gelder, Paul Vitanyi, Chris Wallace, Geoff Webb, Xindong Wu, Jan Zytkow. Inquiries to: isis96@cs.monash.edu.au David Dowe (chair): dld@cs.monash.edu.au Kevin Korb (co-chair): korb@cs.monash.edu.au or Jonathan Oliver (co-chair): jono@cs.monash.edu.au Detailed up-to-date information, including registration costs and further details of speakers, their talks and the tutorials is available on the WWW at: http://www.cs.monash.edu.au/~jono/ISIS/ISIS.shtml - David Dowe, Kevin Korb and Jon Oliver. ======================================================================= From moeller@informatik.uni-bonn.de Wed May 15 19:15:08 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id TAA18232 for ; Wed, 15 May 1996 19:14:50 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id TAA21213 for ; Wed, 15 May 1996 19:14:47 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa22451; 15 May 96 17:43:19 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa22443; 15 May 96 17:20:58 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa29730; 15 May 96 17:20:28 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa04994; 15 May 96 8:29:23 EDT Received: from tethys.informatik.uni-bonn.de by RI.CMU.EDU id aa08115; 15 May 96 8:28:34 EDT Received: from macke.informatik.uni-bonn.de (macke.informatik.uni-bonn.de [131.220.4.117]) by tethys.informatik.uni-bonn.de (8.7.1/8.6.12) with ESMTP id OAA28411; Wed, 15 May 1996 14:14:14 +0200 (MET DST) From: Knut Moeller Received: (moeller@localhost) by macke.informatik.uni-bonn.de (8.7.1/8.6.9) id OAA03722; Wed, 15 May 1996 14:13:54 +0200 (MET DST) Date: Wed, 15 May 1996 14:13:54 +0200 (MET DST) Message-Id: <199605151213.OAA03722@macke.informatik.uni-bonn.de> To: colt@cs.uiuc.edu, connectionists@cs.cmu.edu, intcon@dcs.shef.ac.uk, mafm@cs.uwa.oz.au, genetic@dcs.shef.ac.uk, neuron-request@CATTELL.PSYCH.UPENN.EDU, alife@cognet.ucla.edu, cogpsy@neuro.psy.soton.ac.uk, hybrid-list@cs.ua.edu, annrules@fit.qut.edu.au, ml@ics.uci.edu, Reinforce@cs.uwa.edu.au, gannout@cs.iastate.edu, corryfee%hasara11.BITNET@cunyvm.cuny.edu, csemlist%hasara11.BITNET@cunyvm.cuny.edu, nonlin-l@list.nih.gov, comp-finance@teleport.com, ai-stats-mailing-list@watstat.uwaterloo.ca, genetic-programming@cs.stanford.edu Subject: HeKoNN96-CfP This announcement was sent to various lists. Sorry if you recieved multiple copies. CALL FOR PARTICIPATION ================================================================= = = = H e K o N N 9 6 = = = Autumn School in C o n n e c t i o n i s m and N e u r a l N e t w o r k s October 2-6, 1996 Muenster, Germany Conference Language: German ---------------------------------------------------------------- A comprehensive description of the Autumn School together with abstracts of the courses can be found at the following address: WWW: http://set.gmd.de/AS/fg1.1.2/hekonn = = = O V E R V I E W = = = Artificial neural networks (ANN's) have been discussed in many diverse areas, ranging from models of cortical learning to the control of industrial processes. The goal of the Autumn School in Connectionionism and Neural Networks is to give a comprehensive introduction to connectionism and artificial neural networks (ANN's) and to provide an overview of the current state of the art. Courses will be offered in five thematic tracks. (The conference language is German.) The FOUNDATION track will introduce basic concepts (A. Zell, Univ. Stuttgart) and theoretical issues. Hardwareaspects (U. Rueckert, Univ. Paderborn), Lifelong Learning (G. Paass, GMD St.Augustin), algorithmic complexity of learning procedures (M. Schmitt, TU Graz) and convergence properties of ANN's (K. Hornik, TU Vienna) are presented in further lectures. This year, a special track was devoted to BRAIN RESEARCH. Courses are offered about the simulation of biological neurons (R. Rojas, Univ. Halle), theoretical neurobiology (H. Gluender, LMU Munich), learning and memory (A. Bibbig, Univ. Ulm) and dynamical aspects of cortical information processing (H. Dinse, Univ. Bochum). In the track on SYMBOLIC CONNECTIONISM and COGNITIVE MODELLING, consists of courses on: procedures for extracting rules from ANN's (J. Diederich, QUT Brisbane). representation and cognitive models (G. Peschl, Univ. Vienna), autonomous agents and ANN's (R. Pfeiffer, ETH Zuerich) and hybrid systems (A. Ultsch, Univ. Marburg). APPLICATIONS of ANN's are covered by courses on image processing (H.Bischof, TU Vienna), evolution strategies and ANN's (J. Born, FU Berlin), ANN's and fuzzy logic (R. Kruse, Univ. Braunschweig), and on medical applications (T. Waschulzik, Univ. Bremen). In addition, there will be courses on PROGRAMMING and SIMULATORS. Participants will have the opportunity to work with the SNNS simulator (G. Mamier, A. Zell, Univ. Stuttgart) and the Vienet2/ECANSE simulation tool (G. Linhart, TU Vienna). From ATAXR@asuvm.inre.asu.edu Thu May 16 12:15:38 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id MAA04180 for ; Thu, 16 May 1996 12:15:31 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id MAA02566 for ; Thu, 16 May 1996 12:15:28 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab22451; 15 May 96 17:44:11 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa22445; 15 May 96 17:22:43 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa29743; 15 May 96 17:21:48 EDT Date: Tue, 14 May 1996 13:20:58 -0700 (MST) From: Asim Roy Subject: Connectionist Learning - Some New Ideas To: connectionists@cs.cmu.edu Message-id: <01I4P4L13GWI8X1P3A@asu.edu> Content-transfer-encoding: 7BIT We have recently published a set of principles for learning in neural networks/connectionist models that is different from classical connectionist learning (Neural Networks, Vol. 8, No. 2; IEEE Transactions on Neural Networks, to appear; see references below). Below is a brief summary of the new learning theory and why we think classical connectionist learning, which is characterized by pre-defined nets, local learning laws and memoryless learning (no storing of training examples for learning), is not brain-like at all. Since vigorous and open debate is very healthy for a scientific field, we invite comments for and against our ideas from all sides. "A New Theory for Learning in Connectionist Models" We believe that a good rigorous theory for artificial neural networks/connectionist models should include learning methods that perform the following tasks or adhere to the following criteria: A. Perform Network Design Task: A neural network/connectionist learning method must be able to design an appropriate network for a given problem, since, in general, it is a task performed by the brain. A pre-designed net should not be provided to the method as part of its external input, since it never is an external input to the brain. From a neuroengineering and neuroscience point of view, this is an essential property for any "stand-alone" learning system - a system that is expected to learn "on its own" without any external design assistance. B. Robustness in Learning: The method must be robust so as not to have the local minima problem, the problems of oscillation and catastrophic forgetting, the problem of recall or lost memories and similar learning difficulties. Some people might argue that ordinary brains, and particularly those with learning disabilities, do exhibit such problems and that these learning requirements are the attributes only of a "super" brain. The goal of neuroengineers and neuroscientists is to design and build learning systems that are robust, reliable and powerful. They have no interest in creating weak and problematic learning devices that need constant attention and intervention. C. Quickness in Learning: The method must be quick in its learning and learn rapidly from only a few examples, much as humans do. For example, one which learns from only 10 examples learns faster than one which requires a 100 or a 1000 examples. We have shown that on-line learning (see references below), when not allowed to store training examples in memory, can be extremely slow in learning - that is, would require many more examples to learn a given task compared to methods that use memory to remember training examples. It is not desirable that a neural network/connectionist learning system be similar in characteristics to learners characterized by such sayings as "Told him a million times and he still doesn't understand." On-line learning systems must learn rapidly from only a few examples. D. Efficiency in Learning: The method must be computationally efficient in its learning when provided with a finite number of training examples (Minsky and Papert[1988]). It must be able to both design and train an appropriate net in polynomial time. That is, given P examples, the learning time (i.e. both design and training time) should be a polynomial function of P. This, again, is a critical computational property from a neuroengineering and neuroscience point of view. This property has its origins in the belief that biological systems (insects, birds for example) could not be solving NP-hard problems, especially when efficient, polynomial time learning methods can conceivably be designed and developed. E. Generalization in Learning: The method must be able to generalize reasonably well so that only a small amount of network resources is used. That is, it must try to design the smallest possible net, although it might not be able to do so every time. This must be an explicit part of the algorithm. This property is based on the notion that the brain could not be wasteful of its limited resources, so it must be trying to design the smallest possible net for every task. General Comments This theory defines algorithmic characteristics that are obviously much more brain-like than those of classical connectionist theory, which is characterized by pre-defined nets, local learning laws and memoryless learning (no storing of actual training examples for learning). Judging by the above characteristics, classical connectionist learning is not very powerful or robust. First of all, it does not even address the issue of network design, a task that should be central to any neural network/connectionist learning theory. It is also plagued by efficiency (lack of polynomial time complexity, need for excessive number of teaching examples) and robustness problems (local minima, oscillation, catastrophic forgetting, lost memories), problems that are partly acquired from its attempt to learn without using memory. Classical connectionist learning, therefore, is not very brain-like at all. As far as I know, there is no biological evidence for any of the premises of classical connectionist learning. Without having to reach into biology, simple common sense arguments can show that the ideas of local learning, memoryless learning and predefined nets are impractical even for the brain! For example, the idea of local learning requires a predefined network. Classical connectionist learning forgot to ask a very fundamental question - who designs the net for the brain? The answer is very simple: Who else, but the brain itself! So, who should construct the net for a neural net algorithm? The answer again is very simple: Who else, but the algorithm itself! (By the way, this is not a criticism of constructive algorithms that do design nets.) Under classical connectionist learning, a net has to be constructed (by someone, somehow - but not by the algorithm!) prior to having seen a single training example! I cannot imagine any system, biological or otherwise, being able to construct a net with zero information about the problem to be solved and with no knowledge of the complexity of the problem. (Again, this is not a criticism of constructive algorithms.) A good test for a so-called "brain-like" algorithm is to imagine it actually being part of a human brain. Then examine the learning phenomenon of the algorithm and compare it with that of the human's. For example, pose the following question: If an algorithm like back propagation is "planted" in the brain, how will it behave? Will it be similar to human behavior in every way? Look at the following simple "model/algorithm" phenomenon when the back- propagation algorithm is "fitted" to a human brain. You give it a few learning examples for a simple problem and after a while this "back prop fitted" brain says: "I am stuck in a local minimum. I need to relearn this problem. Start over again." And you ask: "Which examples should I go over again?" And this "back prop fitted" brain replies: "You need to go over all of them. I don't remember anything you told me." So you go over the teaching examples again. And let's say it gets stuck in a local minimum again and, as usual, does not remember any of the past examples. So you provide the teaching examples again and this process is repeated a few times until it learns properly. The obvious questions are as follows: Is "not remembering" any of the learning examples a brain- like phenomenon? Are the interactions with this so-called "brain- like" algorithm similar to what one would actually encounter with a human in a similar situation? If the interactions are not similar, then the algorithm is not brain-like. A so-called brain-like algorithm's interactions with the external world/teacher cannot be different from that of the human. In the context of this example, it should be noted that storing/remembering relevant facts and examples is very much a natural part of the human learning process. Without the ability to store and recall facts/information and discuss, compare and argue about them, our ability to learn would be in serious jeopardy. Information storage facilitates mental comparison of facts and information and is an integral part of rapid and efficient learning. It is not biologically justified when "brain-like" algorithms disallow usage of memory to store relevant information. Another typical phenomenon of classical connectionist learning is the "external tweaking" of algorithms. How many times do we "externally tweak" the brain (e.g. adjust the net, try a different parameter setting) for it to learn? Interactions with a brain-like algorithm has to be brain-like indeed in all respect. The learning scheme postulated above does not specify how learning is to take place - that is, whether memory is to be used or not to store training examples for learning, or whether learning is to be through local learning at each node in the net or through some global mechanism. It merely defines broad computational characteristics and tasks (i.e. fundamental learning principles) that are brain-like and that all neural network/connectionist algorithms should follow. But there is complete freedom otherwise in designing the algorithms themselves. We have shown that robust, reliable learning algorithms can indeed be developed that satisfy these learning principles (see references below). Many constructive algorithms satisfy many of the learning principles defined above. They can, perhaps, be modified to satisfy all of the learning principles. The learning theory above defines computational and learning characteristics that have always been desired by the neural network/connectionist field. It is difficult to argue that these characteristics are not "desirable," especially for self-learning, self- contained systems. For neuroscientists and neuroengineers, it should open the door to development of brain-like systems they have always wanted - those that can learn on their own without any external intervention or assistance, much like the brain. It essentially tries to redefine the nature of algorithms considered to be brain- like. And it defines the foundations for developing truly self- learning systems - ones that wouldn't require constant intervention and tweaking by external agents (human experts) for it to learn. It is perhaps time to reexamine the foundations of the neural network/connectionist field. This mailing list/newsletter provides an excellent opportunity for participation by all concerned throughout the world. I am looking forward to a lively debate on these matters. That is how a scientific field makes real progress. Asim Roy Arizona State University Tempe, Arizona 85287-3606, USA Email: ataxr@asuvm.inre.asu.edu References 1. Roy, A., Govil, S. & Miranda, R. 1995. A Neural Network Learning Theory and a Polynomial Time RBF Algorithm. IEEE Transactions on Neural Networks, to appear. 2. Roy, A., Govil, S. & Miranda, R. 1995. An Algorithm to Generate Radial Basis Function (RBF)-like Nets for Classification Problems. Neural Networks, Vol. 8, No. 2, pp. 179-202. 3. Roy, A., Kim, L.S. & Mukhopadhyay, S. 1993. A Polynomial Time Algorithm for the Construction and Training of a Class of Multilayer Perceptrons. Neural Networks, Vol. 6, No. 4, pp. 535- 545. 4. Mukhopadhyay, S., Roy, A., Kim, L.S. & Govil, S. 1993. A Polynomial Time Algorithm for Generating Neural Networks for Pattern Classification - its Stability Properties and Some Test Results. Neural Computation, Vol. 5, No. 2, pp. 225-238. From cherkaue@cs.wisc.edu Thu May 16 18:49:50 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id SAA11028 for ; Thu, 16 May 1996 18:49:45 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id SAA09308 for ; Thu, 16 May 1996 18:49:43 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa23781; 16 May 96 17:57:10 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa23779; 16 May 96 17:36:34 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00704; 16 May 96 17:36:07 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa29419; 16 May 96 15:26:54 EDT Received: from mozzarella.cs.wisc.edu by CS.CMU.EDU id aa12203; 16 May 96 15:26:39 EDT Received: (from cherkaue@localhost) by mozzarella.cs.wisc.edu (8.6.12/8.6.12) id OAA27944; Thu, 16 May 1996 14:26:37 -0500 Date: Thu, 16 May 1996 14:26:37 -0500 From: Kevin Cherkauer Message-Id: <199605161926.OAA27944@mozzarella.cs.wisc.edu> To: connectionists@cs.cmu.edu Subject: Re: Connectionist Learning - Some New Ideas Cc: cherkaue@mozzarella.cs.wisc.edu In a recent thought-provoking posting to the connectionist list, Asim Roy said: >We have recently published a set of principles for learning in neural >networks/connectionist models that is different from classical >connectionist learning (Neural Networks, Vol. 8, No. 2; IEEE >Transactions on Neural Networks, to appear; ... >E. Generalization in Learning: The method must be able to >generalize reasonably well so that only a small amount of network >resources is used. That is, it must try to design the smallest possible >net, although it might not be able to do so every time. This must be >an explicit part of the algorithm. This property is based on the >notion that the brain could not be wasteful of its limited resources, >so it must be trying to design the smallest possible net for every >task. I disagree with this point. According to Hertz, Krogh, and Palmer (1991, p. 2), the human brain contains about 10^11 neurons. (They also state on p. 3 that "the axon of a typical neuron makes a few thousand synapses with other neurons," so we're looking at on the order of 10^14 "connections" in the brain.) Note that a period of 100 years contains only about 3x10^9 seconds. Thus, if you lived 100 years and learned continuously at a constant rate every second of your life, your brain would be at liberty to "use up" the capacity of about 30 neurons (and 30,000 connections) per second. I would guess this is a very conservative bound, because most of us probably spend quite a bit of time where we aren't learning at such a furious rate. But even using this conservative bound, I calculate that I'm allowed to use up about 2.7x10^6 neurons (and 2.7x10^9 connections) today. I'll try not to spend them all in one place. :-) Dr. Roy's suggestion that the brain must try "to design the smallest possible net for every task" because "the brain could not be wasteful of its limited resources" is unlikely, in my opinion. It seems to me that the brain has rather an abundance of neurons. On the other hand, finding optimal solutions to many interesting "real-world" problems is often very hard computationally. I am not a complexity theorist, but I will hazard to suggest that a constraint on neural systems to be optimal or near-optimal in their space usage is probably both impossible to realize and, in fact, unnecessary. Wild speculation: the brain may have so many neurons precisely so that it can afford to be suboptimal in its storage usage in order to avoid computational time intractability. References Hertz, J.; Krogh, A.; & Palmer, R.G. 1991. Introduction to the Theory of Neural Computation. Redwood City, CA:Addison-Wesley. Roy, A., Govil, S. & Miranda, R. 1995. A Neural Network Learning Theory and a Polynomial Time RBF Algorithm. IEEE Transactions on Neural Networks, to appear. Roy, A., Govil, S. & Miranda, R. 1995. An Algorithm to Generate Radial Basis Function (RBF)-like Nets for Classification Problems. Neural Networks, Vol. 8, No. 2, pp. 179-202. =============================================================================== Kevin Cherkauer cherkauer@cs.wisc.edu From small@cortex.neurology.pitt.edu Fri May 17 14:12:38 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id OAA25495 for ; Fri, 17 May 1996 14:12:32 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id OAA22617 for ; Fri, 17 May 1996 14:12:30 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab24628; 17 May 96 13:24:21 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab24626; 17 May 96 13:05:14 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01651; 17 May 96 13:04:03 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa08208; 17 May 96 8:31:03 EDT Received: from cortex.neurology.pitt.edu by CS.CMU.EDU id aa17308; 17 May 96 8:30:41 EDT Received: by cortex.neurology.pitt.edu; id AA08381; Fri, 17 May 1996 08:30:25 -0400 Message-Id: Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" Date: Fri, 17 May 1996 08:32:44 -0400 To: Kevin Cherkauer From: Steven Small Subject: Re: Connectionist Learning - Some New Ideas Cc: connectionists@cs.cmu.edu >Dr. Roy's suggestion that the brain must try "to design the smallest possible >net for every task" because "the brain could not be wasteful of its limited >resources" is unlikely, in my opinion. It seems to me that the brain has >rather an abundance of neurons. On the other hand, finding optimal solutions to >many interesting "real-world" problems is often very hard computationally. I am >not a complexity theorist, but I will hazard to suggest that a constraint on >neural systems to be optimal or near-optimal in their space usage is probably >both impossible to realize and, in fact, unnecessary. > >Wild speculation: the brain may have so many neurons precisely so that it can >afford to be suboptimal in its storage usage in order to avoid computational >time intractability. I agree with this general idea, although I'm not sure that "computational time intractability" is necessarily the principal reason. There are a lot of good reasons for redundancy, overlap, and space "suboptimality", not the least of which is the marvellous ability at recovery that the brain manifests after both small injuries and larger ones that give pause even to experienced neurologists. -SLS From chris@anvil.co.uk Fri May 17 20:46:28 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id UAA29594 for ; Fri, 17 May 1996 20:46:20 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id UAA27836 for ; Fri, 17 May 1996 20:46:19 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa24628; 17 May 96 13:23:33 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa24626; 17 May 96 13:05:13 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01646; 17 May 96 13:03:35 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa08116; 17 May 96 8:18:06 EDT Received: from [194.193.52.253] by EDRC.CMU.EDU id aa14143; 17 May 96 8:17:34 EDT Received: (from smap@localhost) by gatekeeper (8.6.12/8.6.9) id MAA16154 for ; Fri, 17 May 1996 12:49:42 +0100 Received: from dazzle.anvil.co.uk(194.193.54.13) by wonderwall via smap (V1.3) id sma016145; Fri May 17 12:49:37 1996 Received: from (basl) by anvil.co.uk (4.1/SMI-4.1) id AA01885; Fri, 17 May 96 13:08:24 BST Date: Fri, 17 May 96 13:08:24 BST From: Chris Sharpington Message-Id: <9605171208.AA01885@anvil.co.uk> To: connectionists@cs.cmu.edu Subject: New Book announcement ===================================================================== NEW BOOK ANNOUCEMENT RAPID APPLICATION GENERATION OF BUSINESS AND FINANCE SOFTWARE SUKHDEV KHEBBAL AND CHRIS SHARPINGTON Kluwer Academic Publishers, March 1996 ISBN: 0-7923-9707-X The objectives of the work described in this book were twofold: 1) to capitalise on recent work in object-oriented integration methods to build a Framework for rapid application generation of distributed client-server systems, using the same API on both Microsoft Windows and on Unix 2) to use the Framework to generate real-world applications for intelligent data analysis techniques (neural networks and genetic algorithms) in Finance and Marketing The key requirement was to be able to "plug and play" servers i.e. unplug an Excel forecasting module and plug in a neural network forecasting tool to demonstrate the improved forecasting accuracy. Four applications were built to prove the benefits of the Framework and to demonstrate the value of intelligent techniques for improved data analysis. The application descriptions are accessible to the business manager, interested in the business issues involved, who may have little technical knowledge of neural networks and genetic algorithms. At the same time, technical experts can benefit from the examples of solving real-world application issues. The applications are Direct Marketing (customer targeting and market segmentation), Financial Forecasting, Bankruptcy Predication, and Executive Information Systems. Client-server computing has been attracting great interest of late. However, a server does not have to be a database. The approach in this work has been to standardise the interface to servers and collect a number of different servers together into a Toolkit. Application generation then becomes the rapid and simple process of plugging together the servers required (e.g. data retrieval, data analysis, data display) with a client to control their interaction. The emergence of object-oriented inter-application communication standards such as Object Linking and Embedding (OLE) from Microsoft, and CORBA from the Object Management Group, is fuelling great interest in distributed systems and their commercial benefits. An important contribution of this book is to detail and compare current inter-application communication methods. This will be of great benefit in assessing the potential of each communication method for business application and in assessing the benefits of the HANSA Framework. The work was carried out under Esprit project 6369 HANSA - a collaboration between industrial and academic partners from four European countries, with funding support from the European Commission. Having studied the technical details and illustrations of business value obtained from the Framework, the reader is given details of how to obtain the software, (for both Microsoft Windows and Unix) free of charge from an ftp site. [ There is also a World Wide Web page on The HANSA project: http://www.cs.ucl.ac.uk/hansa ] CONTENTS: ======== Chap 1: Rapid Application Development and the HANSA Project - Sukhdev Khebbal, University College London, UK. - Chris Sharpington, CRL, Hayes, UK. PART ONE: TOOLS FOR RAPID APPLICATION DEVELOPMENT ================================================= Chap 2: The HANSA Framework - Sukhdev Khebbal and Jonthan Ladipo, University College London, UK. Chap 3: THE HANSA Toolkit and The MIMENICE tool - Eric LeSaint, MIMETICS, FRANCE. - Sukhdev Khebbal, University College London, UK. PART TWO: OBJECT-ORIENTED INTEGRATION METHODS ============================================= Chap 4: Survey of Object-Oriented Integration Methods - Sukhdev Khebbal and Jonthan Ladipo, University College London, UK. PART THREE: REAL-WORLD APPLICATIONS =================================== Chap 5: Direct Marketing Application - Chris Sharpington, CRL, Hayes, UK. Chap 6: Banking Application - Thomas Look and Michael Kuhn, IFS, Germany. Chap 7: Bankruptcy Predication Application - Konrad Feldman, Jason Kingdon, Anoop Mangat, SearchSpace Ltd, London. UK. - Renato Arisi, Orsio Romagnoli, O.Group, Rome. ITALY. Chap 8: Executive Information Systems Application - Pierre Charelain and Louis Moussy, Promind, FRANCE. PART FOUR: DEVELOPING HYBRID SYSTEMS ==================================== Chap 9: Evaluating the HANSA Framework - Sukhdev Khebbal and Jonthan Ladipo, University College London, UK. Chap 10: Conclusion and Future Directions - Sukhdev Khebbal, University College London, UK. - Chris Sharpington, CRL, Hayes, UK. ISBN 0-7923-9707-X 212pp HARDBOUND March 1996 Kluwer Academic Publishers, P.O. Box 17, 3300 AA Dordrecht, The Netherlands. TO ORDER THE BOOK ================= Contact your local bookshop or supplier, or direct from the publisher using one of the addresses below: For customers in Mexico, USA, Canada Rest of the world: and Latin America: Kluwer Academic Publishers Kluwer Academic Publishers Order Department Order Department P.O. Box 358 P.O. Box 322 Accord Station 3300 AH Dordrecht Hingham, MA 02018-0358 The Netherlands U.S.A. Tel : 617 871 6600 Tel : +31 78 6392392 Fax : 617 871 6528 Fax : +31 78 6546474 Email : kluwer@wkap.com Email : services@wkap.nl =========================================================== Chris Sharpington (chris@anvil.co.uk) Anvil Software Ltd, 51-53 Rivington Street, London EC2A 3QQ tel +44 171 729 8036 fax +44 171 729 5067 From Jonathan_Stein@comverse.com Fri May 17 20:46:29 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id UAA29596 for ; Fri, 17 May 1996 20:46:22 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id UAA27838 for ; Fri, 17 May 1996 20:46:21 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa24871; 17 May 96 18:21:07 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa24869; 17 May 96 18:06:56 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01770; 17 May 96 18:06:29 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa14686; 17 May 96 16:48:33 EDT Received: from crux.comverse.com by RI.CMU.EDU id aa21277; 17 May 96 16:48:07 EDT Received: from hub.comverse.com ([204.240.7.8]) by comverse.com (5.x/SMI-SVR4) id AA24941; Fri, 17 May 1996 16:39:44 -0400 Received: from ccMail by hub.comverse.com (SMTPLINK V2.10.08) id AA832376960; Fri, 17 May 96 16:42:44 EST Date: Fri, 17 May 96 16:42:44 EST From: Jonathan_Stein@comverse.com Encoding: 31 Text Message-Id: <9604178323.AA832376960@hub.comverse.com> To: cherkaue@cs.wisc.edu, Steven Small Cc: connectionists@cs.cmu.edu Subject: Re[2]: Connectionist Learning - Some New Ideas > >I agree with this general idea, although I'm not sure that "computational >time intractability" is necessarily the principal reason. There are a lot >of good reasons for redundancy, overlap, and space "suboptimality", not the >least of which is the marvellous ability at recovery that the brain >manifests after both small injuries and larger ones that give pause even to >experienced neurologists. > One needn't draw upon injuries to prove the point. One loses about 100,000 cortical neurons a day (about a percent of the original number every three years) under normal conditions. This loss is apparently not significant for brain function. This has been often called the strongest argument for distributed processing in the brain. Compare this ability with the fact that single conductor disconnection cause total system failure with high probability in conventional computers. Although certainly acknowledged by the pioneers of artificial neural network techniques, very few networks designed and trained by present techniques are anywhere near that robust. Studies carried out on the Hopfield model of associative memory DO show graceful degradation of memory capacity with synapse dilution under certain conditions (see eg. DJ Amit's book "Attractor Neural Networks"). Synapse pruning has been applied to trained feedforward networks (eg. LeCun's "Optimal Brain Damage") but requires retraining of the network. JS From dnoelle@cs.ucsd.edu Sat May 18 05:42:15 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id FAA05131 for ; Sat, 18 May 1996 05:42:09 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id FAA01373 for ; Sat, 18 May 1996 05:42:07 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa25388; 18 May 96 2:44:20 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa25386; 18 May 96 2:36:31 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00865; 18 May 96 2:34:42 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa28873; 16 May 96 14:50:30 EDT Received: from odin.ucsd.edu by EDRC.CMU.EDU id aa10747; 16 May 96 14:49:43 EDT Received: from hilbert.ucsd.edu by odin.ucsd.edu; id AA18827 sendmail 8.73/UCSDPSEUDO.4-CS via SMTP Thu, 16 May 96 11:49:32 -0700 for connectionists@cs.cmu.edu Received: by hilbert (5.67/UCSDPSEUDO.4) id AA14585 for connectionists@cs.cmu.edu; Thu, 16 May 96 11:49:11 -0700 Date: Thu, 16 May 96 11:49:11 -0700 From: David Noelle Message-Id: <9605161849.AA14585@hilbert> To: connectionists@cs.cmu.edu Subject: CogSci96 Extension ************************************************ ***** EARLY REGISTRATION DEADLINE EXTENDED ***** ************************************************ Eighteenth Annual Conference of the COGNITIVE SCIENCE SOCIETY July 12-15, 1996 University of California, San Diego La Jolla, California SECOND CALL FOR PARTICIPATION The early registration deadline for Cognitive Science '96 has been extended to June 1, 1996. If you register now, you can still get the low early registration rates! (If you have already paid for registration at the higher "late" rates, the difference will be reimbursed to you at the conference.) Also, affordable on-campus housing is still available on a first-come first-served basis. An electronic registration form and the complete conference schedule appear below. Further information may be found on the web at "http://www.cse.ucsd.edu/events/cogsci96/". When scheduling plane flights, note that the conference begins on Friday evening, July 12th, and ends late on Monday afternoon, July 15th. If you want to attend all conference events, you should plan on staying the nights of the 12th through the 15th. Register today! * PLENARY SESSIONS * "Controversies in Cognitive Science: The Case of Language" -+-+- Stephen Crain (UMD College Park) & Mark Seidenberg (USC) Moderated by Paul Smolensky (Johns Hopkins University) "Tenth Anniversary of the PDP Books" -+-+- "Affect and Neuro-modulators: A Connectionist Account" Dave Rumelhart (Stanford) "Parallel-Distributed Processing Models of Normal and Disordered Cognition" Jay McClelland (CMU) "Why Neural Networks Need Generative Models" Geoff Hinton (Toronto) "Frontal Lobe Development and Dysfunction in Children: Dissociations between Intention and Action" -+-+- Adele Diamond (MIT) "Reconstructing Consciousness" -+-+- Paul Churchland (UCSD) * SYMPOSIA * "Adaptive Behavior and Learning in Complex Environments" "Building a Theory of Problem Solving and Scientific Discovery: How Big is N in N-Space Search?" "Cognitive Linguistics: Mappings in Grammar, Conceptual Systems, and On-Line Meaning Construction" "Computational Models of Development" "Evolution of Language" "Evolution of Mind" "Eye Movements in Cognitive Science" "The Future Of Modularity" "The Role of Rhythm in Cognition" "Update on the Plumbing of Cognition: Brain Imaging Studies of Vision, Attention, and Language" * PAPER PRESENTATION SESSIONS * Analogy Categories, Concepts, and Mutability Cognitive Neuroscience Development Distributed Cognition and Education Lexical Ambiguity and Semantic Representation Perception Perception of Causality Philosophy Problem-Solving and Education Reasoning Recurrent Network Models Rhythm in Cognition Semantics, Phonology, and the Lexicon Skill Learning and SOAR Text Comprehension Visual/Spatial Reasoning REGISTRATION INFORMATION There are three ways to register for the 1996 Cognitive Science Conference: * ONLINE REGISTRATION -- You may fill out and electronically submit the online registration form, which may be found on the conference web page at "http://www.cse.ucsd.edu/events/cogsci96/". This is the preferred method of registration. (You must pay registration fees with a Visa or MasterCard in order to use this option.) * EMAIL REGISTRATION -- You may fill out the plain text (ASCII) registration form, which appears below, and send it via electronic mail to "cogsci96reg@cs.ucsd.edu". (You must pay registration fees with a Visa or MasterCard in order to use this option.) * POSTAL REGISTRATION -- You may download a copy of the PostScript registration form from the conference home page (or extract the plain text version, below), print it on a PostScript printer, fill it out with a pen, and send it via postal mail to: CogSci'96 Conference Registration Cognitive Science Department - 0515 University of California, San Diego 9500 Gilman Drive La Jolla, CA 92093-0515 (Under this option, you may enclose payment of registration fees in U. S. dollars in the form of a check or money order, or you may pay these fees with a Visa or MasterCard. Please make checks payable to: The Regents of the University of California.) For more information, visit the conference web page at "http://www.cse.ucsd.edu/events/cogsci96". Please direct questions and comments to "cogsci96@cs.ucsd.edu", (619) 534-6773, or (619) 534-6776. Edwin Hutchins and Walter Savitch, Conference Chairs John D. Batali, Local Arrangements Chair Garrison W. Cottrell, Program Chair ====================================================================== PLAIN TEXT REGISTRATION FORM ====================================================================== Cognitive Science 1996 Registration Form ---------------------------------------- Your Full Name : _____________________________________________________ Your Postal Address : ________________________________________________ (including zip/postal ________________________________________________ code and country) ________________________________________________ ________________________________________________ Your Telephone Number (Voice) : ______________________________________ Your Telephone Number (Fax) : ______________________________________ Your Internet Electronic Mail Address (e.g., dnoelle@cs.ucsd.edu) : ______________________________________________________________________ REGISTRATION FEES : Please select the appropriate registration option from the menu below by placing an "X" in the corresponding blank on the left. Note that the Cognitive Science Society is offering a special deal to individuals who opt to join the Society simultaneously with conference registration. The "New Member" package includes conference fees and first year's membership dues for only $10 more than the nonmember conference cost. Registration fees received after June 1st are $20 higher ($10 higher for students) than fees received before June 1st. Be sure to register early to take advantage of the lower fee rates. _____ Registration, Member -- $120 ($140 after June 1st) _____ Registration, Nonmember -- $145 ($165 after June 1st) _____ Registration, New Member -- $155 ($175 after June 1st) _____ Registration, Student Member -- $85 ($95 after June 1st) _____ Registration, Student Nonmember -- $100 ($110 after June 1st) _____ Registration, New Student Member -- $115 ($125 after June 1st) CONFERENCE BANQUET : Tickets to the conference banquet are *not* included in the registration fees, above. Banquet tickets are $35 per person. (You may bring guests.) Number Of Banquet Tickets Desired ($35 each): _____ _____ Omnivorous _____ Vegetarian CONFERENCE SHIRTS : Conference T-Shirts are *not* included in the registration fees, above. These are $10 each. Number Of T-Shirts Desired ($10 each): _____ UCSD ON-CAMPUS APARTMENTS : There are a limited number of on-campus apartments available for reservation as a 4 night package, from July 12th through July 16th. Included is a (mandatory) meal plan - cafeteria breakfast (4 days), and lunch (3 days). The total cost is $191 per person (double occupancy, including tax) and $227 per person (single occupancy, including tax). (Checking in a day early is $45 extra for a single room or $36 for a double.) On campus parking is complimentary with this package. Off-campus accommodations in local hotels are also available, but you will need to make reservations by contacting the hotel of interest directly. If you will be staying off-campus, please skip this portion of the registration form. On-campus housing reservations must be received by June 1st, 1996. Please include the cost of on-campus housing in the total conference cost listed at the bottom of this form. Select the housing plan desired by placing an "X" in the appropriate blank on the left: _____ UCSD Housing and Meal Plan (Single Room) -- $227 per person _____ UCSD Housing and Meal Plan (Double Room) -- $191 per person Arrival Date And Time : ____________________________________________ Departure Date And Time : ____________________________________________ If you reserved a double room above, please indicate your roommate preference below: _____ Please assign a roommate to me. I am _____ female _____ male. _____ I will be sharing this room with a guest who is not registered for the conference. I will include $382 ($191 times 2) in the total conference cost listed at the bottom of this form. _____ I will be sharing this room with another conference attendee. I will include $191 in the total conference cost listed at the bottom of this form. My roommate will submit her housing fee along with her registration form. My roommate's full name is: ______________________________________________________________ ASL TRANSLATION : American Sign Language (ASL) translators will be available for a number of conference events. The number of translated events will be, in part, a function of the number of participants in need of this service. Please indicate below if you will require ASL translation of conference talks. _____ I will require ASL translation. Comments To The Registration Staff : ______________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ Please sum your conference registration fees, the cost of banquet tickets and t-shirts, and on-campus housing costs, and place the total below. To register by electronic mail, payment must be by Visa or MasterCard only. TOTAL : _$____________ Bill to: _____ Visa _____ MasterCard Number : ___________________________________________ Expiration Date: ___________________________________ Registration fees (including on-campus housing costs) will be fully refunded if cancellation is requested prior to May 1st. If registration is cancelled between May 1st and June 1st, 20% of paid fees will be retained by the Society to cover processing costs. No refunds will be granted after June 1st. When complete, send this form via email to "cogsci96reg@cs.ucsd.edu". Please direct questions to "cogsci96@cs.ucsd.edu", (619) 534-6773, or (619) 534-6776. ====================================================================== PLAIN TEXT REGISTRATION FORM ====================================================================== =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*= TENTATIVE SCHEDULE OF EVENTS The conference check-in/registration desk will be located at the UCSD Price Center at the times listed in the schedule below. On-site registration, conference packets, and names tags will be available there. FRIDAY EVENING, JULY 12, 2:00 P.M. - 9:00 P.M. REGISTRATION (PRICE CENTER THEATER LOBBY) FRIDAY EVENING, JULY 12, 7:00 P.M. - 8:30 P.M. PLENARY SESSION "Controversies In Cognitive Science: The Case Of Language" Stephen Crain (UMD College Park) & Mark Seidenberg (USC) Moderated by Paul Smolensky (Johns Hopkins University) FRIDAY EVENING, JULY 12, 8:30 P.M. WELCOMING RECEPTION SATURDAY MORNING, JULY 13, 7:30 A.M. - 5:00 P.M. REGISTRATION (PRICE CENTER BALLROOM LOBBY) SATURDAY MORNING, JULY 13, 8:30 A.M. - 10:00 A.M. SUBMITTED SYMPOSIUM "Building A Theory Of Problem Solving And Scientific Discovery: How Big Is N In N-Space Search?" Bruce Burns (Organizer) Lisa Baker & Kevin Dunbar Bruce Burns & Regina Vollmeyer Chris Schunn & David Klahr David F. Wolf II & Jonathan R. Beskin SUBMITTED SYMPOSIUM "The Role Of Rhythm In Cognition" Devin McAuley (Organizer) Mari Jones Bill Baird Robert Port Elliot Saltzman PAPER PRESENTATIONS - PHILOSOPHY "Beyond Computationalism" Giunti, Marco "Qualia: The Hard Problem" Griffith, Todd W. ; Byrne, Michael "Connectionism, Systematicity, And Nomic Necessity" Hadley, Robert F. "Fodor On Information And Computation" Brook, Andrew ; Stainton, Robert SATURDAY MORNING, JULY 13, 10:30 A.M. - 12:20 P.M. SUBMITTED SYMPOSIUM "The Future Of Modularity" Michael Spivey-Knowlton (Organizer) Kathleen Eberhard (Organizer) Michael Tanenhaus (Organizer) James McClelland Peter Lennie Robert Jacobs Kenneth Forster Dominic Massaro Gary Dell PAPER PRESENTATIONS - TEXT COMPREHENSION "Integrating World Knowledge With Cognitive Parsing" Paredes-Frigolett, Harold ; Strube, Gerhard "The Role Of Ontology In Creative Understanding" Moorman, Kenneth ; Ram, Ashwin "Working Memory In Text Comprehension: Interrupting Difficult Text" McNamara, Danielle ; Kintsch, Walter "Reasoning From Multiple Texts: An Automatic Analysis Of Readers' Situation Models" Foltz, Peter ; Britt, M. Anne ; Perfetti, Charles "Lexical Limits On The Influence Of Context" Verspoor, Cornelia PAPER PRESENTATIONS - REASONING "Dynamics Of Rule Induction By Making Queries: Transition Between Strategies" Ginzburg, Iris ; Sejnowksi, Terry "The Impact Of Information Representation On Bayesian Reasoning" Hoffrage, Ulrich ; Gigerenzer, Gerd "On Reasoning With Default Rules And Exceptions" Elio, Renee ; Pelletier, Francis "Satisficing Inference And The Perks Of Ignorance" Goldstein, Daniel G. ; Gigerenzer, Gerd "A Connectionist Treatment Of Negation And Inconsistency" Shastri, Lokendra ; Grannes, Dean SATURDAY, JULY 13, 12:20 P.M. - 2:00 P.M. LUNCH & POSTER PREVIEW SATURDAY, JULY 13, 2:00 P.M. - 3:30 P.M. INVITED SYMPOSIUM "Update On The Plumbing Of Cognition: Imaging Studies Of Vision, Attention, And Language" Helen Neville (Organizer) Marty Sereno Steven Hillyard PAPER PRESENTATIONS - DISTRIBUTED COGNITION AND EDUCATION "Hearing With Eyes: A Distributed Cognition Perspective On Guitar Song Imitation" Flor, Nick V. ; Holder, Barbara "Constraints On The Experimental Design Process In Real-World Science" Baker, Lisa M. ; Dunbar, Kevin "Teaching/Learning Events In The Workplace: A Comparative Analysis Of Their Organizational And Interactional Structure" Hall, Rogers ; Stevens, Reed "Distributed Reasoning: An Analysis Of Where Social And Cognitive Worlds Fuse" Dama, Mike ; Dunbar, Kevin PAPER PRESENTATIONS - DEVELOPMENT I "Reading And Learning To Classify Letters" Martin, Gale "Where Defaults Don't Help: The Case Of The German Plural System" Nakisa, Ramin Charles ; Hahn, Ulrike "Selective Attention In The Acquisition Of The Past Tense" Jackson, Dan ; Constandse, Rodger ; Cottrell, Garrison "Word Learning And Verbal Short-Term Memory: A Computational Account" Gupta, Prahlad SATURDAY, JULY 13, 4:00 P.M. - 5:30 P.M. PLENARY SESSION "Tenth Anniversary Of The PDP Books" "Affect and Neuro-modulators: A Connectionist Account" Dave Rumelhart (Stanford) "Parallel-Distributed Processing Models Of Normal And Disordered Cognition" Jay McClelland (CMU) "Why Neural Networks Need Generative Models" Geoff Hinton (Toronto) SATURDAY, JULY 13, 5:30 P.M. - 7:30 P.M. POSTER SESSION & RECEPTION SATURDAY, JULY 13, 9:00 P.M. - 1:00 A.M. BLUES PARTY SUNDAY, JULY 14, 7:30 A.M. - 5:00 P.M. REGISTRATION (PRICE CENTER BALLROOM LOBBY) SUNDAY, JULY 14, 8:30 A.M. - 10:00 A.M. SUBMITTED SYMPOSIUM "Evolution Of Mind" Denise Dellarosa Cummins (Organizer) John Tooby Colin Allen PAPER PRESENTATIONS - VISUAL/SPATIAL REASONING "Spatial Cognition In The Mind And In The World - The Case Of Hypermedia Navigation" Dahlback, Nils ; Hook, Kristina ; Sjolinder, Marie "Individual Differences In Proof Structures Following Multimodal Logic Teaching" Oberlander, Jon ; Cox, Richard ; Monaghan, Padraic ; Stenning, Keith ; Tobin, Richard "Functional Roles For The Cognitive Analysis Of Diagrams In Problem Solving" Cheng, Peter C-H. "A Study Of Visual Reasoning In Medical Diagnosis" Rogers, E. PAPER PRESENTATIONS - SEMANTICS, PHONOLOGY, AND THE LEXICON "The Interaction Of Semantic And Phonological Processing" Tyler, Lorraine K. ; Voice, J. Kate ; Moss, Helen E. "The Combinatorial Lexicon: Affixes As Processing Structures" Marslen-Wilson, William ; Ford, Mike ; Older, Lianne ; Zhou, Xiaolin "Lexical Ambiguity And Context Effects In Spoken Word Recognition: Evidence From Chinese" Li, Ping ; Yip, C. W. "Phonological Reduction, Assimilation, Intra-Word Information Structure, And The Evolution Of The Lexicon Of English" Shillcock, Richard ; Hicks, John ; Cairns, Paul ; Chater, Nick ; Levy, Joseph SUNDAY, JULY 14, 10:30 A.M. - 12:20 P.M. INVITED SYMPOSIUM "Adaptive Behavior and Learning in Complex Environments" Maja Mataric (Organizer) Simon Giszter Andrew Moore Sebastian Thrun PAPER PRESENTATIONS - PERCEPTION "Color Influences Fast Scene Categorization" Oliva, Aude ; Schyns, Philippe "Categorical Perception Of Novel Dimensions" Goldstone, Robert L. ; Steyvers, Mark ; Larimer, Ken "Categorical Perception In Facial Emotion Classification" Padgett, Curtis ; Cottrell, Garrison "MetriCat: A Representation For Basic And Subordinate-Level Classification" Stankiewicz, Brian J. ; Hummel, John E. "Similarity To Reference Shapes As A Basis For Shape Representation" Edelman, Shimon ; Cutzu, Florin ; Duvdevani-Bar, Sharon PAPER PRESENTATIONS - LEXICAL AMBIGUITY AND SEMANTIC REPRESENTATION "Integrating Discourse And Local Constraints In Resolving Lexical Thematic Ambiguities" Hanna, Joy E. ; Spivey-Knowlton, Michael ; Tanenhaus, Michael "Evidence For A Tagging Model Of Human Lexical Category Disambiguation" Corley, Steffan ; Crocker, Matt "The Importance Of Automatic Semantic Relatedness Priming For Distributed Models Of Word Meaning" McRae, Ken ; Boisvert, Stephen "Parallel Activation Of Distributed Concepts: Who Put The P In The PDP?" Gaskell, M. Gareth "Discrete Multi-Dimensional Scaling" Clouse, Daniel ; Cottrell, Garrison SUNDAY, JULY 14, 12:20 P.M. - 2:00 P.M. LUNCH & SOCIETY BUSINESS MEETING SUNDAY, JULY 14, 2:00 P.M. - 3:30 P.M. INVITED SYMPOSIUM "Cognitive Linguistics: Mappings in Conceptual Systems, Grammar, and Meaning Construction" Gilles Fauconnier (Organizer) George Lakoff Ron Langacker PAPER PRESENTATIONS - PROBLEM-SOLVING AND EDUCATION "Collaboration In Primary Science Classroom: Learning About Evaporation" Scanlon, Eileen ; Murphy, Patricia ; Issroff, Kim ; Hodgson, Barbara ; Whitelegg, Elizabeth "Transferring And Modifying Terms In Equations" Catrambone, Richard "Understanding Constraint-Based Processes: A Precursor To Conceptual Change In Physics" Slotta, James ; Chi, T. H. Michelene "The Role Of Generic Modeling In Conceptual Change" Griffith, Todd W. ; Nersessian, Nancy ; Goel, Ashok PAPER PRESENTATIONS - RECURRENT NETWORK MODELS "Using Orthographic Neighborhoods Of Interlexical Nonwords To Support An Interactive-Activation Model Of Bilingual Memory" French, Robert M. ; Ohnesorge, Clark "Conscious And Unconscious Perception: A Computational Theory" Mathis, Donald ; Mozer, Michael "In Search of Articulated Attractors" Noelle, David ; Cottrell, Garrison "A Recurrent Network That Performs A Context-Sensitive Prediction Task" Steijvers, Mark ; Grunwald, Peter SUNDAY, JULY 14, 4:00 P.M. - 5:30 P.M. PLENARY SESSION "Frontal Lobe Development And Dysfunction In Children: Dissociations Between Intention And Action" Adele Diamond (MIT) SUNDAY, JULY 14, 6:00 P.M. - 9:00 P.M. CONFERENCE BANQUET MONDAY, JULY 15, 8:30 A.M. - 10:00 A.M. SUBMITTED SYMPOSIUM "Eye Movements In Cognitive Science" Patrick Suppes (Organizer) Julie Epelboim (Organizer) Eileen Kowler Mary Hayhoe Greg Zelinsky PAPER PRESENTATIONS - ANALOGY "Competition In Analogical Transfer: When Does A Lightbulb Outshine An Army?" Francis, Wendy ; Wickens, Thomas "Can A Real Distinction Be Made Between Cognitive Theories Of Analogy And Categorisation" Ramscar, Michael ; Paint, Helen "LISA: A Computational Model Of Analogical Inference And Schema Induction" Hummel, John E. ; Holyoak, Keith J. "Alignability And Attribute Important In Choice" Lindermann, Patricia ; Markman, Arthur PAPER PRESENTATIONS - DEVELOPMENT II "A Computational Model Of Two Types Of Developmental Dyslexia" Harm, Michael ; Seidenberg, Mark "Integrating Multiple Cues In Word Segmentation: A Connectionist Model Using Hints" Allen, Joe ; Christiansen, Morten "Statistical Cues In Language Acquisition: Word Segmentation By Infants" Saffran, Jenny R. ; Aslin, Richard N. ; Newport, Elissa "Perceptual Laws And The Statistics Of Natural Signals" Movellan, Javier ; Chadderdon, George MONDAY, JULY 15, 10:30 A.M. - 12:20 P.M. SUBMITTED SYMPOSIUM "Computational Models Of Development" Kim Plunkett (Organizer) Tom Shultz (Organizer) Jeff Elman Charles Ling Denis Mareschal Liz Bates (Discussant) Jeff Shrager (Discussant) PAPER PRESENTATIONS - SKILL LEARNING AND SOAR "An Abstract Computational Model Of Learning Selective Sensing Skills" Langley, Pat "Epistemic Action Increases With Skill" Maglio, Paul ; Kirsh, David "Perseverative Subgoaling And Production System Models Of Problem Solving" Cooper, Richard "Probabilistic Plan Recognition For Cognitive Apprenticeship" Conati, Cristina ; VanLehn, Kurt "Do Users Interact With Computers The Way Our Models Say They Should?" Vera, Alonso H. ; Lewis, Richard PAPER PRESENTATIONS - RHYTHM IN COGNITION "Rhythmic Commonalities Between Hand Gestures And Speech" Cummins, Fred ; Port, Robert "Modeling Beat Perception With A Nonlinear Oscillator" Large, Edward W. PAPER PRESENTATIONS - COGNITIVE NEUROSCIENCE "Emotional Decisions" Barnes, Allison ; Thagard, Paul "Self-Organization And Functional Role Of Lateral Connections And Multisize Receptive Fields In The Primary Visual Cortex" Sirosh, Joseph, Miikkulainen, Risto "Synaptic Maintenance Through Neuronal Homeostasis: A Function Of Dream Sleep" Horn, David ; Levy, Nir ; Ruppin, Eytan MONDAY, JULY 15, 12:20 P.M. - 2:00 P.M. LUNCH MONDAY, JULY 15, 2:00 P.M. - 3:30 P.M. INVITED SYMPOSIUM "Evolution Of Language" John Batali (Organizer) David Ackley (Organizer) Domenico Parisi (not confirmed) PAPER PRESENTATIONS - PERCEPTIONS OF CAUSALITY "The Perception Of Causality: Feature Binding In Interacting Objects" Kruschke, John K. ; Fragasi, Michael "Judging The Contingency Of A Constant Cue: Contrasting Predictions From An Associative And A Statistical Model" Vallee-Tourangeau, F. ; Murphy, Robin ; Baker, A. G. "What Language Might Tell Us About The Perception Of Cause" Wolff, Phillip PAPER PRESENTATIONS - CATEGORIES, CONCEPTS, AND MUTABILITY "Mutability, Conceptual Tranformation, And Context" Love, Bradley C. "On Putting Milk In Coffee: The Effect Of Thematic Relations On Similarity Judgments" Wisniewski, Edward ; Bassok, Mariam "The Role Of Situations In Concept Learning" Yeh, Wenchi ; Barsalou, Lawrence "Modeling Interference Effects In Instructed Category Learning" Noelle, David ; Cottrell, Garrison MONDAY, JULY 15, 4:00 P.M. - 5:30 P.M. PLENARY SESSION "Reconstructing Consciousness" Paul Churchland (UCSD) =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*= From rao@cs.rochester.edu Sat May 18 23:32:04 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id XAA12150 for ; Sat, 18 May 1996 23:31:59 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id XAA06158 for ; Sat, 18 May 1996 23:31:57 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa26512; 18 May 96 22:40:13 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa26510; 18 May 96 22:26:20 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02916; 18 May 96 22:24:34 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa27400; 18 May 96 14:15:05 EDT Received: from cayuga.cs.rochester.edu by RI.CMU.EDU id aa24170; 18 May 96 14:14:21 EDT Received: from skunk.cs.rochester.edu (skunk.cs.rochester.edu [192.5.53.143]) by cayuga.cs.rochester.edu (8.6.9/H) with ESMTP id OAA17661; Sat, 18 May 1996 14:14:16 -0400 Received: (from rao@localhost) by skunk.cs.rochester.edu (8.6.9/K) id OAA09391; Sat, 18 May 1996 14:14:13 -0400 Date: Sat, 18 May 1996 14:14:13 -0400 From: rao@cs.rochester.edu Message-Id: <199605181814.OAA09391@skunk.cs.rochester.edu> To: Jonathan_Stein@comverse.com CC: cherkaue@cs.wisc.edu, small@cortex.neurology.pitt.edu, connectionists@cs.cmu.edu In-reply-to: <9604178323.AA832376960@hub.comverse.com> (Jonathan_Stein@comverse.com) Subject: Re: Re[2]: Connectionist Learning - Some New Ideas >One loses about 100,000 cortical neurons a day (about a percent of >the original number every three years) under normal conditions. Does anyone have a concrete citation (a journal article) for this or any other similar estimate regarding the daily cell death rate in the cortex of a normal brain? I've read such numbers in a number of connectionist papers but none cite any neurophysiological studies that substantiate these numbers. Thanks, Raj -- Raj Rao Internet: rao@cs.rochester.edu Dept. of Computer Science VOX: (716) 275-2527 University of Rochester FAX: (716) 461-2018 Rochester NY 14627-0226 WWW: http://www.cs.rochester.edu/u/rao/