From gerda@ai.univie.ac.at Mon Jul 24 19:02:33 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Mon, 24 Jul 95 19:02:30 -0500; AA01273 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Mon, 24 Jul 95 19:02:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa09267; 24 Jul 95 17:18:01 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa09218; 24 Jul 95 16:31:06 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa16158; 24 Jul 95 16:29:46 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa10186; 24 Jul 95 8:03:02 EDT Received: from kairo.ai.univie.ac.at by RI.CMU.EDU id aa04890; 24 Jul 95 8:01:37 EDT Received: by kairo.ai.univie.ac.at id AA05709 (5.65c8/IDA-1.4.4 for connectionists@cs.cmu.edu); Mon, 24 Jul 1995 13:59:40 +0100 Date: Mon, 24 Jul 1995 13:59:40 +0100 From: Gerda Helscher Message-Id: <199507241259.AA05709@kairo.ai.univie.ac.at> To: connectionists@cs.cmu.edu Subject: Symposium "ANN and Adaptive Systems" CALL FOR PAPERS for the symposium ====================================================== Artificial Neural Networks and Adaptive Systems ====================================================== chairs: Guenter Palm, Germany, and Georg Dorffner, Austria as part of the Thirteenth European Meeting on Cybernetics and Systems Research April 9-12, 1996 University of Vienna, Vienna, Austria For this symposium, papers on any theoretical or practical aspect of artificial neural networks are invited. Special focus, however, will be put on the issue of adaptivity both in practical engineering applications and in applications of neural networks to the modeling of human behavior. By adaptivity we mean the capability of a neural network to adjust itself to changing environments. We make a careful distinction between "learning" to devise weight matrices for a neural network before it is applied (and usually left unchanged) on one hand, and true adaptivity of a given neural network to constantly changing con- ditions on the other hand - i.e. incremental learning in unstat- ionary environments. The following is a - no means exhaustive - list of possible topics in this realm: - online or incremental learning of neural network applications facing changing data distributions - transfer of neural network solutions to related but different approaches - application of neural networks in adaptive autonomous systems - "phylogenetic" vs. "ontogenetic" adaptivity (e.g. adaptivity of connectivity and architecture vs. adaptivity of coupling parameters or weights) - short term vs. long term adaptation - adaptive reinforcement learning - adaptive pattern recognition - localized vs. distributed approximation (in terms of overlap of decision regions) and adaptivity Preference will be given to contributions that address such issues of adaptivity, but - as mentioned initially - other original work on neural newtorks is also welcome. Deadline for submissions (10 single-spaced A4 pages, maximum 43 lines, max. line length 160 mm, 12 point) is =============================================== October 12, 1995 =============================================== Papers should be sent to: I. Ghobrial-Willmann or G. Helscher Austrian Society for Cybernetic Studies A-1010 Vienna 1, Schottengasse 3 (Austria) Phone: +43-1-53532810 Fax: +43-1-5320652 E-mail: sec@ai.univie.ac.at For more information on the whole EMCSR conference, see the Web-page http://www.ai.univie.ac.at/emcsr/ or contact the above address. !Hope to see you in Vienna! From Dimitris.Dracopoulos@trurl.brunel.ac.uk Mon Jul 24 19:02:34 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Mon, 24 Jul 95 19:02:31 -0500; AA01278 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Mon, 24 Jul 95 19:02:29 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab09267; 24 Jul 95 17:18:52 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab09218; 24 Jul 95 16:31:17 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa16163; 24 Jul 95 16:30:13 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa10531; 24 Jul 95 8:37:28 EDT Received: from sirius.brunel.ac.uk by EDRC.CMU.EDU id aa19309; 24 Jul 95 8:37:05 EDT Received: from trurl.brunel.ac.uk by sirius.brunel.ac.uk with SMTP (PP) id <17865-0@sirius.brunel.ac.uk>; Mon, 24 Jul 1995 13:33:41 +0100 Received: by trurl.brunel.ac.uk (940816.SGI.8.6.9/940406.SGI.AUTO) id NAA07789; Mon, 24 Jul 1995 13:32:07 +0200 From: Dimitris Dracopoulos Message-Id: <9507241332.ZM7787@trurl.brunel.ac.uk> Date: Mon, 24 Jul 1995 13:32:05 -0600 Reply-To: Dimitris.Dracopoulos@brunel.ac.uk X-Mailer: Z-Mail (3.2.1 6apr95 MediaMail) To: connectionists@cs.cmu.edu, genetic-programming@CS.Stanford.EDU, GA-List@AIC.NRL.NAVY.MI Subject: NEURAL AND EVOLUTIONARY SYSTEMS ADVANCED MSC Mime-Version: 1.0 Content-Type: text/plain; charset=us-ascii NEURAL AND EVOLUTIONARY SYSTEMS ADVANCED MSC ============================================ The Computer Science Department at Brunel University (United Kingdom) will be running a new advanced MSc course on Neural and Evolutionary Systems from September 1995. You may find further details at the following locations: WWW: http://http1.brunel.ac.uk:8080/depts/cs/ in the News section FTP: ftp.brunel.ac.uk CompSci/Announcements/NES-MSc.ps (PostScript version) CompSci/Announcements/NES-MSc.ascii (ASCII version) For further information including literature and an application form, please contact Pam Osborne at the address below, or for more detailed enquiries please contact Vlatka Hlupic (address given below) or me via email at: Dr Dimitris C. Dracopoulos Department of Computer Science Brunel University Telephone: +44 1895 274000 ext. 2120 London Fax: +44 1895 251686 Uxbridge E-mail: Dimitris.Dracopoulos@brunel.ac.uk Middlesex UB8 3PH United Kingdom ------------------------------------------------------------------------------- Pam Osborne Dept of Computer Science Tel: +44 (0)895 274000 Brunel University Ext: 2134 Uxbridge Fax: +44 (0)895 251686 Middlesex UB8 3PH Pam.Osborne@brunel.ac.uk ------------------------------------------------------ ------------------------------------------------------ Dr. Vlatka Hlupic Dept of Computer Science Tel: +44 (0)895 274000 Brunel University Ext: 2231 Uxbridge Fax: +44 (0)895 251686 Middlesex UB8 3PH Vlatka.Hlupic@brunel.ac.uk -- Dr Dimitris C. Dracopoulos Department of Computer Science Brunel University Telephone: +44 1895 274000 ext. 2120 London Fax: +44 1895 251686 Uxbridge E-mail: Dimitris.Dracopoulos@brunel.ac.uk Middlesex UB8 3PH United Kingdom From tirthank@titanic.mpce.mq.edu.au Tue Jul 25 02:41:01 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 25 Jul 95 02:40:57 -0500; AA05325 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 25 Jul 95 02:40:55 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa09216; 24 Jul 95 17:07:06 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa09214; 24 Jul 95 16:29:48 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa16152; 24 Jul 95 16:29:20 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa08748; 24 Jul 95 5:42:15 EDT Received: from macadam.mpce.mq.edu.au by EDRC.CMU.EDU id aa18916; 24 Jul 95 5:41:44 EDT Received: from titanic.mpce.mq.edu.au by macadam.mpce.mq.edu.au (5.64+/1.1) id AA26938; Mon, 24 Jul 95 19:39:19 +1000 Received: from krakatoa.mpce.mq.edu.au. by titanic.mpce.mq.edu.au (4.1/SMI-4.1) id AA07999; Mon, 24 Jul 95 19:39:18 EST From: Tirthankar Raychaudhuri Message-Id: <9507240939.AA07999@titanic.mpce.mq.edu.au> Subject: Change to URL of Combining Estimators Page To: connectionists@cs.cmu.edu Date: Mon, 24 Jul 1995 19:39:18 +1000 (EST) X-Mailer: ELM [version 2.4 PL22] Content-Type: text Content-Length: 748 Hi all, It was gratifying to note how much response my Web page for Combining Estimators has evoked. Thank you for all your suggestions. I have incorporated (or am in the process of incorporating) most of them, including the addition of references which I have missed earlier. Please note If you have a reference you need to add, what I'd most appreciate is a URL link to the paper. If this is not available then of course the journal/conference proceedings/other reference must suffice. The URL for the page has changed slightly as of this morning. It's now "http://www-comp.mpce.mq.edu.au/~tirthank/combest.html". In other words we have a new alias `www-comp' for our server. Thank you once again for your interest. Tirthankar RayChaudhuri From M.Q.Brown@ecs.soton.ac.uk Tue Jul 25 12:24:39 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 25 Jul 95 12:24:37 -0500; AA10544 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 25 Jul 95 12:24:34 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ac09267; 24 Jul 95 17:19:44 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa09232; 24 Jul 95 16:56:36 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa16192; 24 Jul 95 16:55:38 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa12813; 24 Jul 95 11:03:07 EDT Received: from beech.soton.ac.uk by EDRC.CMU.EDU id aa19807; 24 Jul 95 11:01:52 EDT Received: from bright.ecs.soton.ac.uk (bright.ecs.soton.ac.uk [152.78.64.201]) by beech.soton.ac.uk (8.6.12/hub-8.5a) with SMTP id QAA17075 for ; Mon, 24 Jul 1995 16:01:06 +0100 Received: from isis.ecs.soton.ac.uk by bright.ecs.soton.ac.uk; Mon, 24 Jul 95 16:00:17 BST From: Martin Brown Date: Mon, 24 Jul 1995 15:49:17 +0000 Message-Id: <6371.9507241449@ra.ecs.soton.ac.uk> To: Connectionists@cs.cmu.edu Subject: 2 postdoctoral positions available X-Sun-Charset: US-ASCII Content-Length: 4351 UNIVERSITY OF SOUTHAMPTON DEPARTMENT OF ELECTRONICS AND COMPUTER SCIENCE RESEARCH FELLOWS Two postdoctoral positions are currently available on an EPSRC grant entitled Neurofuzzy Construction Algorithms and their Application in Non-Stationary Environments. Links to the groups, personnel and industrial companies can be obtained from the project's homepage at: http://www-isis.ecs.soton.ac.uk/research/projects/osiris.html Two postdoctoral researchers are required to investigate the development and application of advanced network construction algorithms and training rules for neurofuzzy systems operating in a time-varying environment. The candidates should possess skills in applied mathematics and computer science and have experience in such areas as numerical analysis, Visual C++ programming, neural/fuzzy learning theory, dynamical systems and optimisation theory. This research will be undertaken in association with Neural Computer Sciences http://www.demon.co.uk/skylake/ who produce an object oriented, 32 bit MS windows-based neural networks package called NeuFrame and benchmarking data sets will be collected from GEC and Lucas. In addition, Eurotherm controls are supplying tools to investigate the possibility of developing embedded devices. Post One - One researcher is required for 3 years to investigate and further develop the neurofuzzy construction algorithms that have been proposed by the ISIS group. They will be based at Southampton under the supervision of Martin Brown and Chris Harris. The neural+fuzzy approach allows vague, expert knowledge to be combined with numerical data to produce systems that make the best use of both information sources. However, for ill-defined, high-dimensional systems it would be useful to configure a network's structural parameters directly from the data. Recent research has shown that B-spline-based neurofuzzy systems are suitable for use in such algorithms due to their direct fuzzy interpretation, numerical conditioning and ease of implementation, and by considering an ANalysis Of VAriance (ANOVA) representation, the B-spline neurofuzzy networks can be shown to overcome the curse of dimensionality for many practical problems. A good background in numerical analysis and modelling theory (additive, neural/fuzzy) is required, and as the algorithms will be developed within a Visual C++, Microsoft Foundation Classes environment, hence knowledge about these products would also be useful. Informal enquiries for this post should be made to Dr Martin Brown in the ISIS research group, Department of Electronics and Computer Science, University of Southampton, UK (Tel +44 (0)1703 594984, Email: mqb@ecs.soton.ac.uk). Salary will be in the range of 15,986 - 18,985 per annum. Applicants for post one should send a full curriculum vitae (3 copies from UK applicants and 1 from overseas), including the names and addresses of three referees to the Personnel Department (R), University of Southampton, Highfield, Southampton, SO17 1BJ, telephone number (01703 592750) by no later than 25 August 1995. Please quote reference number R/553. Post Two - A second researcher is required for 2 years (with the possibility of it being extended for an extra year) to investigate on-line learning for non-stationary data. They will be based at Brighton University under the supervision of Steve Ellacott. This work will investigate several aspects of training neurofuzzy systems on-line such as: * learning algorithms for large, redundant training sets * recurrent training rules * high-order instantaneous learning algorithms * aspects of data excitation and on-line regularisation The ideal candidate would be a mathematician or mathematically oriented engineer with a background in numerical analysis and/or dynamical systems. Familiarity with neural network algorithms would be an advantage, but is not essential. The post will involve some programming in C or C++. All enquiries and applications for post two should be made to Dr Steve Ellacott in the Department of Mathematical Sciences, University of Brighton, UK (Tel +44 (0)1273 642544, Email: s.w.ellacott@brighton.ac.uk). working for equal opportunities a centre of excellence for university research and teaching From eann96@lpac.qmw.ac.uk Tue Jul 25 21:43:44 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 25 Jul 95 21:43:41 -0500; AA17226 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 25 Jul 95 21:43:38 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa10711; 25 Jul 95 16:51:46 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa10709; 25 Jul 95 16:32:20 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa17320; 25 Jul 95 16:31:52 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa21184; 25 Jul 95 9:43:34 EDT Received: from epsilon.qmw.ac.uk by CS.CMU.EDU id aa03153; 25 Jul 95 9:39:12 EDT Received: from ganymede.lpac.ac.uk by epsilon.qmw.ac.uk with SMTP-DNS (PP) id <12282-0@epsilon.qmw.ac.uk>; Tue, 25 Jul 1995 14:27:50 +0100 From: Engineering Apps in Neural Nets 96 Received: from pluto by ganymede.lpac.qmw.ac.uk; Tue, 25 Jul 1995 13:53:26 +0100 Original-Via: Pp-Warning: Illegal Via field on preceding line Date: Tue, 25 Jul 95 13:53:07 +0100 Message-Id: <9433.9507251253@pluto.lpac.qmw.ac.uk> To: connectionists@cs.cmu.edu Subject: EANN96-First Call for Papers International Conference on Engineering Applications of Neural Networks (EANN '96) London, UK June 24-26, 1996 First Call for Papers (ASCII version) The conference is a forum for presenting the latest results on neural network applications in technical fields. The applications may be in any engineering or technical field, including but not limited to systems engineering, mechanical engineering, robotics, process engineering, metallurgy, pulp and paper technology, aeronautical engineering, computer science, machine vision, chemistry, chemical engineering, physics, electrical engineering, electronics, civil engineering, geophysical sciences, biotechnology, and environmental engineering. Abstracts of one page (200 to 400 words) should be sent to eann96@lpac.ac.uk by 21 January 1996, by e-mail in PostScript format, or ASCII. Please mention two to four keywords, and whether you prefer it to be a short paper or a full paper. The short papers will be 4 pages in length, and full papers may be upto 8 pages. Tutorial proposals are also welcome until 21 January 1996. Notification of acceptance will be sent around 15 February. Submissions will be reviewed and the number of full papers will be very limited. Organising Committee A. Bulsari (Finland) Dimitris Tsaptsinos (UK) Trevor Clarkson (UK) International program committee (to be confirmed, extended) Dorffner, Georg (Austria) Gong, Shaogang (UK) Heikkonen, Jukka (Italy) Jervis, Barrie (UK) Oja, Erkki (Finland) Liljenstrom, Hans (Sweden) Papadourakis, George (Greece) Pham, D.T (UK) Refenes, Paul (UK) Sharkey, Noel (UK) Steele, Nigel (UK) Williams, Dave (UK) For more information see the WWW Page at:http://www.lpac.ac.uk/EANN96/ From FRYRL@f1groups.fsd.jhuapl.edu Tue Jul 25 21:43:49 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 25 Jul 95 21:43:46 -0500; AA17234 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 25 Jul 95 21:43:41 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab10740; 25 Jul 95 17:11:30 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab10713; 25 Jul 95 16:33:18 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa17333; 25 Jul 95 16:33:00 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id ab26623; 25 Jul 95 15:37:35 EDT Received: from mailer.jhuapl.edu by EDRC.CMU.EDU id aa25760; 25 Jul 95 15:20:58 EDT Received: from fsdsmtpgw.jhuapl.edu by mailer.jhuapl.edu (5.65/DEC-Ultrix/4.3) id AA23374; Tue, 25 Jul 1995 15:20:19 -0400 Received: by fsdsmtpgw.fsd.jhuapl.edu with Microsoft Mail id <3014B770@fsdsmtpgw.fsd.jhuapl.edu>; Tue, 25 Jul 95 15:20:48 EDT From: "Fry, Robert L." To: Connectionists Subject: NNs and Info. Th. Date: Tue, 25 Jul 95 15:18:00 EDT Message-Id: <3014B770@fsdsmtpgw.fsd.jhuapl.edu> Encoding: 68 TEXT X-Mailer: Microsoft Mail V3.0 New neuroprose entry: A paper entitled "Rational neural models based on information theory" will be preseted at the Fifteenth International Workshop on MAXIMUM ENTROPY AND BAYESIAN METHODS, in Sante Fe, New Mexico on July 31 - August 4, 1995. The enclosed abstract summarizes the presentation which describes an information-theoretic explanation of some spatial and temporal aspects of neurological information processing. Author: Robert L. Fry Affiliation: The Johns Hopkins University/Applied Physics Laboratory Laurel, MD 20723 Title: Rational neural models based on information theory Abstract Biological organisms which possess a neurological system exhibit varying degrees of what can be termed rational behavior. One can hypothesize that rational behavior and thought processes in general arise as a consequence of the intrinsic rational nature of the neurological system and its constituent neurons. A similar statement may be made of the immunological system [1]. The concept of rational behavior can be made quantitative. In particular, one possible characterization of rational behavior is as follows (1) A physical entity (observer) must exist which has the capacity for both measurement and the generation of outputs (participation). Outputs represent decisions on the part of the observer which will be seen to be rational. (2) The establishment of the quantities measurable by the observer is achieved through learning. Learning characterizes the change in knowledge state of an observer in response to new information and is driven by the directed divergence information measure of Kullback [2]. (3) Output decisions must be made optimally on the basis of noisy and/or missing input data. Optimally here implies that the decision-making process must abide by the standard logical consistency axioms which give rise to probability as the only logically consistent measure of degree of plausible belief. An observer using decision rules based on such is said to be rational. Information theory can be used to quantify the above leading to computational paradigms with architectures that closely resemble both the single cortical neuron and interconnected planar field of multiple cortical neurons all of which are functionally identical to one another. A working definition of information in a neural context must be agreed upon prior to this development, however. Such a definition can be obtained through the Laws of Form - a mathematics of observation originating with the British mathematician George Spencer-Brown [3]. [1] Francisco J. Varela, Principles of Biological Autonomy, North Holland, 1979. [2] Solomon Kullback, Information theory and statistics, Wiley, 1959 and Dover, 1968. [3] George Spencer-Brown, Laws of Form, E. P. Dutton, New York 1979 The paper is in compressed postscript format via FTP from archive.cis.ohio-state.edu /pub/neuroprose/fry.maxent.ps.Z using standard telnet or other FTP procedures From baluja@GS93.SP.CS.CMU.EDU Tue Jul 25 21:43:51 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 25 Jul 95 21:43:48 -0500; AA17240 Message-Id: <9507260243.AA12907@lucy.cs.wisc.edu> Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 25 Jul 95 21:43:45 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ac10740; 25 Jul 95 17:12:25 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa10730; 25 Jul 95 16:44:17 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa17345; 25 Jul 95 16:44:06 EDT Received: from GS93.SP.CS.CMU.EDU by B.GP.CS.CMU.EDU id aa27878; 25 Jul 95 16:34:54 EDT From: Shumeet Baluja Date: Tue, 25 Jul 95 16:33:20 EDT To: connectionists@cs.cmu.edu Subject: Paper Available on Human Face Detection Cc: baluja@cs.cmu.edu, har@cs.cmu.edu Title: Human Face Detection in Visual Scenes By: Henry Rowley, Shumeet Baluja & Takeo Kanade Abstract: We present a neural network-based face detection system. A retinally connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We use a bootstrapping algorithm for training the networks, which adds false detections into the training set as training progresses. This eliminates the difficult task of manually selecting non-face training examples, which must be chosen to accurately represent the entire space of non-face images. The system out-performs other state-of-the-art face detection systems, in terms of detection and false-positive rates. Instructions (via WWW) ---------------------------------------------- PAPER (html & postscript) is available from both of these sites: http://www.cs.cmu.edu/~baluja http://www.cs.cmu.edu/~har ON-LINE DEMO: http://www.ius.cs.cmu.edu/demos/facedemo.html QUESTIONS and COMMENTS (please mail to both): baluja@cs.cmu.edu & har@cs.cmu.edu From jbower@bbb.caltech.edu Wed Jul 26 14:07:09 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Wed, 26 Jul 95 14:07:05 -0500; AA29284 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Wed, 26 Jul 95 14:07:01 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa10740; 25 Jul 95 17:10:33 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa10713; 25 Jul 95 16:33:17 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa17328; 25 Jul 95 16:32:25 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa24244; 25 Jul 95 12:48:11 EDT Received: from smaug-gw.caltech.edu by CS.CMU.EDU id aa05036; 25 Jul 95 12:46:46 EDT Received: from bbb.caltech.edu (smaug.bbb.caltech.edu) by gateway.bbb.caltech.edu (4.1/SMI-4.0) id AA00103; Tue, 25 Jul 95 09:55:02 PDT Received: from [131.215.137.84] (gatorbox4.bbb.caltech.edu) by bbb.caltech.edu (4.1/SMI-4.1) id AA17150; Tue, 25 Jul 95 09:54:44 PDT Date: Tue, 25 Jul 95 09:54:43 PDT Message-Id: <9507251654.AA17150@bbb.caltech.edu> Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" To: Connectionists@cs.cmu.edu From: jbower@bbb.caltech.edu Subject: CNS*94 Conference Proceedings The Neurobiology of Computation edited by James M. Bower CALTECH, Pasadena, CA, USA The Neurobiology of Computation: The Proceedings of the Third Annual Computation and Neural Systems Conference contains the collected papers of the Conference on Computational Neuroscience, July 21--23, 1994, Monterey, California. These papers represent a cross-section of current research in computational neuroscience. While the majority of papers describe analysis and modeling efforts, other papers describe the results of new biological experiments explicitly placed in the context of computational theories and ideas. Subjects range from an analysis of subcellular processes, to single neurons, networks, behavior, and cognition. In addition, several papers describe new technical developments of use to computational neuroscientists. Contents: Introduction. Section 1: Subcellular. Section 2: Cellular. Section 3: Network. Section 4: Systems. Index. Kluwer Academic Publishers, Boston Date of publishing: July 1995 464 pp. Hardbound ISBN: 0-7923-9543-3 Prices: NLG: 300.00 USD: 180.00 GBP: 122.50 ============================================================================= ORDER FORM Author: James M. Bower Title: The Neurobiology of Computation ( ) Hardbound / ISBN: 0-7923-9543-3 NLG: 300.00 USD: 180.00 GBP: 122.50 Ref: KAPIS ( ) Payment enclosed to the amount of ___________________________ ( ) Please send invoice ( ) Please charge my credit card account: Card no.: |_|_|_|_|_|_|_|_|_|_|_|_|_|_|_|_| Expiry date: ______________ () Access () American Express () Mastercard () Diners Club () Eurocard () Visa Name of Card holder: ___________________________________________________ Delivery address: Title : ___________________________ Initials: _______________M/F______ First name : ______________________ Surname: ______________________________ Organization: ______________________________________________________________ Department : ______________________________________________________________ Address : ______________________________________________________________ Postal Code : ___________________ City: ____________________________________ Country : _____________________________Telephone: ______________________ Email : ______________________________________________________________ Date : _____________________ Signature: _____________________________ Our European VAT registration number is: |_|_|_|_|_|_|_|_|_|_|_|_|_|_| To be sent to: For customers in Mexico, USA, Canada Rest of the world: and Latin America: Kluwer Academic Publishers Kluwer Academic Publishers Group 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 392392 Fax : 617 871 6528 Fax : +31 78 546474 Email : kluwer@wkap.com Email : services@wkap.nl After October 10, 1995 Tel : +31 78 6392392 Fax : +31 78 6546474 Payment will be accepted in any convertible currency. Please check the rate of exchange with your bank. Prices are subject to change without notice. All prices are exclusive of Value Added Tax (VAT). Customers in the Netherlands please add 6% VAT. Customers from other countries in the European Community: * please fill in the VAT number of your institute/company in the appropriate space on the orderform: or * please add 6% VAT to the total order amount (customers from the U.K. are not charged VAT). *************************************** James M. Bower Division of Biology Mail code: 216-76 Caltech Pasadena, CA 91125 (818) 395-6817 (818) 449-0679 FAX NCSA Mosaic addresses for: laboratory http://www.bbb.caltech.edu/bowerlab GENESIS: http://www.bbb.caltech.edu/GENESIS science education reform http://www.caltech.edu/~capsi From terry@salk.edu Wed Jul 26 23:24:31 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Wed, 26 Jul 95 23:24:27 -0500; AA05349 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Wed, 26 Jul 95 23:24:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa10952; 25 Jul 95 19:26:55 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa10950; 25 Jul 95 19:15:59 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa17436; 25 Jul 95 19:15:16 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa28251; 25 Jul 95 16:56:05 EDT Received: from helmholtz.salk.edu by CS.CMU.EDU id aa07813; 25 Jul 95 16:55:40 EDT Received: by salk.edu (4.1/SMI-4.1) id AA26263; Tue, 25 Jul 95 13:55:28 PDT Date: Tue, 25 Jul 95 13:55:28 PDT From: Terry Sejnowski Message-Id: <9507252055.AA26263@salk.edu> To: connectionists@cs.cmu.edu Subject: Development: A Constructivist Manifesto Cc: steve@salk.edu, terry@salk.edu FTP-host: archive.cis.ohio-state.edu FTP-file: pub/neuroprose/quartz.const.ps.Z The file quartz.const.ps.Z is now available for copying from the Neuroprose repository. This is a 47 page paper. No hardcopies available. THE NEURAL BASIS OF COGNITIVE DEVELOPMENT: A CONSTRUCTIVIST MANIFESTO by Steven R. Quartz and Terrence J. Sejnowski The Salk Institute for Biological Studies PO Box 85800, San Diego CA 92186-5800 e-mail: steve@salk.edu submitted to: Behavioral and Brain Science ABSTRACT: Through considering the neural basis of cognitive development, we present a constructivist view. Its key feature is that environmentally-derived activity regulates neuronal growth as a progressive increase in the representational capacities of cortex. Learning in development becomes a dynamic interaction between the environment's informational structure and growth mechanisms, allowing the representational properties of cortex to be constructed by the problem domain confronting it. This is a uniquely powerful and general learning strategy that undermines the central assumptions of classical learnability theory. It also minimizes the need for prespecification of cortical function, suggesting that cortical evolution is a progression to more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in specialized, innate circuits. ************ How to obtain a copy of the paper ************* Via Anonymous FTP: unix> ftp archive.cis.ohio-state.edu Name: anonymous Password: (type your email address) ftp> cd pub/neuroprose ftp> binary ftp> get quartz.const.ps.Z ftp> quit unix> uncompress quartz.const.ps.Z unix> lpr quartz.const.ps.Z (or what you normally do to print PostScript) From marco@McCulloch.Ing.UniFI.IT Wed Jul 26 23:24:32 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Wed, 26 Jul 95 23:24:28 -0500; AA05351 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Wed, 26 Jul 95 23:24:26 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa11007; 25 Jul 95 19:37:37 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab10950; 25 Jul 95 19:16:01 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa17443; 25 Jul 95 19:15:43 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa28637; 25 Jul 95 17:10:34 EDT Received: from cesit1.unifi.it by CS.CMU.EDU id aa03602; 25 Jul 95 10:32:52 EDT Received: from McCulloch.Ing.UniFI.IT by CESIT1.UNIFI.IT (PMDF V4.3-7 #3688) id <01HTAEH5CBFK000GBH@CESIT1.UNIFI.IT>; Tue, 25 Jul 1995 13:20:53 MET Received: by McCulloch.Ing.UniFI.IT (5.x/SMI-SVR4) id AA14789; Tue, 25 Jul 1995 13:20:22 +0200 Date: Tue, 25 Jul 1995 13:20:22 +0200 From: Marco Gori Subject: paper announcement To: Connectionists@cs.cmu.edu Message-Id: <9507251120.AA14789@McCulloch.Ing.UniFI.IT> Organization: DSI - University of Florence (Italy) Content-Transfer-Encoding: 7BIT X-Sun-Charset: US-ASCII FTP-host: spovest.ing.unifi.it FTP-file: pub/tech-reports/bank.ps.Z FTP-file: pub/tech-reports/num-pla.ps.Z The following papers are now available by anonymous ftp. They have been submitted to ICANN95 - Industrial track. In particular, the first one describes BANK, a real machine for banknote recognition, while the second one reports the results of a software tool for the recognition of number-plates in motorway environments. ================================================================ BANK: A Banknote Acceptor with Neural Kernel A. Frosini(*), M. Gori(**), and P. Priami(*) (*) Consulting Engineer (**) DSI - Univ. Firenze (ITALY) Abstract This paper gives a summary of the electronics and software modules of BANK, a banknote machine operating by a neural network-based recognition model. The machine perceives banknotes by means of low cost optoelectronic devices which produce signals associated with the reflected and refracted rays of two parallel strips in the banknote. The recognition model is based on multilayer networks acting for both the classification and verification steps. ================================================================== Number-Plate Recognition in Practice: The role of Neural Networks A. Frosini, M. Gori(*), L. Pistolesi (*) DSI - Univ. Firenze (ITALY) Abstract The automatic number-plate recognition has been receiving a growing attention in practice in a number of different problems. In this paper we show the crucial role of neural networks for implementing a software tool for the recognition of number-plates in the actual motor way environment for Italian cars. We show that proper neural network architectures can solve the problem of character recognition very effectively and, most importantly, can also offer a significant confidence on the the classification decision. This turns out to be of crucial importance in order to exploit effectively the hypothesize and verify paradigm on which the software tool relies. P.S. A demo of the software tool will be available via internet in the next few weeks for Personal Computers. ================================================================== From rmeir@ee.technion.ac.il Thu Jul 27 03:39:35 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 27 Jul 95 03:39:27 -0500; AA07550 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 27 Jul 95 03:39:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa12368; 26 Jul 95 11:48:51 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa12366; 26 Jul 95 11:24:55 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa18123; 26 Jul 95 11:24:49 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa11669; 26 Jul 95 7:03:01 EDT Received: from ee.technion.ac.il by RI.CMU.EDU id aa13303; 26 Jul 95 7:02:12 EDT Received: (from rmeir@localhost) by ee.technion.ac.il (8.6.12/8.6.6) id OAA25777 for Connectionists@CS.CMU.EDU; Wed, 26 Jul 1995 14:00:50 -0200 Date: Wed, 26 Jul 1995 14:00:50 -0200 From: Ron Meir Message-Id: <199507261600.OAA25777@ee.technion.ac.il> To: Connectionists@cs.cmu.edu Subject: 12th Israeli Symposium on AI, CV & NN -------- Announcement and Call For Papers ------------ 12th Israeli Symposium on Artificial Intelligence, Computer Vision and Neural Networks Tel Aviv University, Tel Aviv, February 4-5, 1996 The purpose of the symposium is to bring together researchers and practitioners from Israel and abroad who are interested in the areas of Artificial Intelligence, Computer Vision, and Neural Networks, and to promote interaction between them. The program will include contributed as well as invited lectures and possibly some tutorials. All lectures will be given in English. Papers are solicited addressing all aspects of AI, Computer Vision and Neural Networks. Novel contributions in preliminary stages are especially encouraged but significant work which has been presented recently will also be considered. The symposium is intended to be more informal than previous symposia. The proceedings, including summaries of the contributed and invited talks, will be organized as a technical report and distributed during the symposium. No copyright will be required. To minimize costs, we intend to organize this symposium on a university campus. Authors should submit an extended abstract of their presentation in English so that it will reach us by September 1st 1995. Submissions should be limited to four pages, including title and bibliography. Submitted contributions will be refereed by the program committee. Authors will be notified of acceptance by November 1st, 1995. A final abstract, to be included in the proceedings, is due by January 10, 1996. For receiving updated information on the symposium, please send a message to Yvonne Sagi (yvonne@cs.technion.ac.il), including your name, affiliation, e-mail, fax number and phone number. Submitted extended abstracts should be send to: Yvonne Sagi Computer Science Department Technion, Israel Institute of Technology Haifa, 32000, Israel Dan Geiger (Artificial Intelligence) e-mail: dang@cs.technion.ac.il Phone: 972-4-294265 Micha Lindenbaum (Computer Vision) e-mail: mic@cs.technion.ac.il Phone: 972-4-294331 Ron Meir (Neural Networks) e-mail: rmeir@ee.technion.ac.il Phone: 972-4-294658 From gordon@aic.nrl.navy.mil Thu Jul 27 08:54:56 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 27 Jul 95 08:54:53 -0500; AA10202 Received: from bilby.cs.uwa.oz.au by lucy.cs.wisc.edu; Thu, 27 Jul 95 08:54:49 -0500 Received: from (mafm@parma.cs.uwa.oz.au [130.95.1.7]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id QAA05975; Thu, 27 Jul 1995 16:53:09 +0800 Message-Id: <199507270853.QAA05975@cs.uwa.oz.au> From: gordon@aic.nrl.navy.mil To: reinforce@cs.uwa.edu.au Cc: gordon@aic.nrl.navy.mil Subject: special journal issue Date: Wed, 26 Jul 95 15:51:05 EDT The upcoming July/August issue of Machine Learning journal is a special issue on "Bias Evaluation and Selection." We believe the topic of bias is relevant to all forms of machine learning. The issue begins with an introductory article that formalizes the definitions of representational and procedural bias. It then presents a framework for bias shifting. Although the introductory article is expressed in terms of supervised concept learning, the definitions and framework should be easily extendible to any type of learning. The remainder of the issue consists of articles about biases in different types of learning (supervised concept learning, ILP, speedup learning). We hope this issue will: 1) provide interesting and informative reading, 2) encourage people in other areas of machine learning not represented in this issue (e.g., reinforcement learning, cognitive learning, evolutionary computation) to apply the definitions and methodologies presented in this issue to their areas of expertise, and 3) encourage further research on bias and other unifying themes that are of central concern to all of machine learning (e.g., Tom Dietterich's ML95 paper on unifying EBL and RL is a similar step in this direction). Diana Gordon Marie desJardins Editors From C.Campbell@bristol.ac.uk Thu Jul 27 20:38:58 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 27 Jul 95 20:38:54 -0500; AA17164 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 27 Jul 95 20:38:52 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa14667; 27 Jul 95 19:04:34 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa14663; 27 Jul 95 18:48:18 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa19261; 27 Jul 95 18:47:58 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa03065; 27 Jul 95 5:39:29 EDT Received: from dira.bris.ac.uk by CS.CMU.EDU id aa22303; 27 Jul 95 5:38:57 EDT Received: from zeus.bris.ac.uk by dira.bris.ac.uk with SMTP (PP); Thu, 27 Jul 1995 10:25:28 +0100 Received: by zeus.bris.ac.uk (950215.SGI.8.6.10/940406.SGI) for Connectionists@cs.cmu.edu id KAA11419; Thu, 27 Jul 1995 10:25:27 +0100 From: I C G Campbell Message-Id: <199507270925.KAA11419@zeus.bris.ac.uk> Subject: PhD studentship available To: Connectionists@cs.cmu.edu Date: Thu, 27 Jul 1995 10:25:27 +0100 (BST) X-Mailer: ELM [version 2.4 PL21] Mime-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit Content-Length: 1310 PhD Studentship Available A PhD studentship has become available at short notice. The project involves the application of neural computing and statistical techniques to highlight and detect tumours on scans. In particular we are interested in detecting a specific type of tumour called an acoustic neuroma. The project is in collaboration with staff from the Computer Science Dept., Bristol University with an interest in computer vision and staff from the Dept. of Radiology, Bristol Royal Infirmary. The closing date for applications is the ** 12th August 1995 **. The studentship is available for three years with a maintenance grant of 5,000 pounds per annum and coverage of postgraduate fees at the home rate of 2,200 pounds per annum. Suitable candidates should have a First or Upper Second Class degree in computer science or mathematics or a similar numerate discipline. Interested candidates should contact Dr. Colin Campbell, Dept. of Engineering Mathematics, Bristol University, Bristol BS8 1TR, United Kingdom. Given the close deadline it is best to contact Dr. Campbell via e-mail (C.Campbell@bris.ac.uk). Candidates should send a CV and arrange for 2 letters of reference to be despatched to the above address ASAP. From howse@baku.eece.unm.edu Thu Jul 27 20:39:03 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 27 Jul 95 20:38:57 -0500; AA17170 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 27 Jul 95 20:38:54 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab14694; 27 Jul 95 19:15:33 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab14671; 27 Jul 95 18:49:59 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa19272; 27 Jul 95 18:49:19 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id ab16339; 27 Jul 95 18:01:22 EDT Received: from baku.eece.unm.edu by CS.CMU.EDU id aa28763; 27 Jul 95 17:59:19 EDT Return-Path: Received: by baku.eece.unm.edu (4.1/VISION/14Apr88/C) id AA03634; Thu, 27 Jul 95 15:59:15 MDT Posted-Date: Thu, 27 Jul 1995 15:59:09 -0600 Message-Id: <9507272159.AA03634@baku.eece.unm.edu> To: connectionists@cs.cmu.edu Reply-To: howse@eece.unm.edu Subject: Tech Report Available Date: Thu, 27 Jul 1995 15:59:09 -0600 From: El Confundido The following technical report is available by FTP: A Synthesis of Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks James W. Howse, Chaouki T. Abdallah and Gregory L. Heileman Abstract The process of model learning can be considered in two stages: model selection and parameter estimation. In this paper a technique is presented for constructing dynamical systems with desired qualitative properties. The approach is based on the fact that an n-dimensional nonlinear dynamical system can be decomposed into one gradient and (n - 1) Hamiltonian systems. Thus, the model selection stage consists of choosing the gradient and Hamiltonian portions appropriately so that a certain behavior is obtainable. To estimate the parameters, a stably convergent learning rule is presented. This algorithm is proven to converge to the desired system trajectory for all initial conditions and system inputs. This technique can be used to design neural network models which are guaranteed to solve certain classes of nonlinear identification problems. Retrieval: FTP anonymous to: ftp.eece.unm.edu cd howse get techrep.ps.gz This is a PostScript file compressed with gzip. The paper is 28 pages long and formatted to print DOUBLE-sided. This paper has been submitted for publication. If there are any retrieval problems please let me know. I would welcome any comments or suggestions regarding the paper. =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= James Howse - howse@eece.unm.edu __ __ __ __ _ _ /\ \/\ \/\ \/\ \/\ `\_/ `\ University of New Mexico \ \ \ \ \ \ `\\ \ \ \ Department of EECE, 224D \ \ \ \ \ \ , ` \ \ `\_/\ \ Albuquerque, NM 87131-1356 \ \ \_\ \ \ \`\ \ \ \_',\ \ Telephone: (505) 277-0805 \ \_____\ \_\ \_\ \_\ \ \_\ FAX: (505) 277-1413 or (505) 277-1439 \/_____/\/_/\/_/\/_/ \/_/ =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= From d23d@unb.ca Thu Jul 27 20:39:04 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 27 Jul 95 20:39:00 -0500; AA17175 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 27 Jul 95 20:38:56 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ac14694; 27 Jul 95 19:16:41 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa14676; 27 Jul 95 18:50:49 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa19277; 27 Jul 95 18:50:17 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa16405; 27 Jul 95 18:05:02 EDT Received: from hermes.csd.unb.ca by RI.CMU.EDU id aa20352; 27 Jul 95 18:03:24 EDT Received: from jupiter.sun.csd.unb.ca by unb.ca (8.6.12/950414-15:35) id TAA19837; Thu, 27 Jul 1995 19:03:11 -0300 Received: by jupiter.sun.csd.unb.ca (8.6.10/950215-16:05) id TAA11986; Thu, 27 Jul 1995 19:03:10 -0300 Date: Thu, 27 Jul 1995 19:03:09 -0300 (ADT) From: Deshpande X-Sender: d23d@jupiter To: connectionists@cs.cmu.edu Subject: Some Questions ... Message-Id: Mime-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII Dear Members, We are currently working on a symbolic approach to low level processing of visual information. There may be many researchers in this list who might be working in this area of vision. I would like to pose certain very basic questions whose importance was often overlooked. Let me first in simple terms put forth the problem that we working on: Is the information processing in low level vision symbolic or non-symbolic? That is, should the signal that the measurement devices capture be interpreted symbolically or , as conventionally being followed, in the functional domain. And what are the implications of the two initial forms of representation as far as pattern recognition is considered? Some of the related work can be found in [1]. Moreover, 1) What is the justification for a spatial/frequency domain decomposition of the signal (intensity-map) that is representing the objects ? 2) Through an information theoretic point of veiw, what relevance does this decomposition have ? 3) Neurophysiological evidence does show a similarity to a Gabor filtering scheme in the human visual system , but as David Marr had rightly pointed out, how does this help one to understand its specific relationship to perception ? 4) Even if one assumes an ad hoc justification for the above (spatial- frequency based decomposition), how does one justify the distance function imposed on the vector space formed by these basis functions (of gabor filters), that is, how does this distance function bring out the relationship between the geometrical information of objects that the signal is representing? One finds a lot of literature on this approach of spatial-frequency domain decompostion of the signal as a scheme for texture segmentation, but none really justifies the appropriateness of this approach. If the above is not of relevance to the majority of the members please send your suggestions and comments directly to the following email address: d23d@unb.ca . cheers, sanjay [1] I.B.Muchnik and V.V Mottl, "Linguistic Analysis of Experimental Curves", Proc. IEEE, vol 67, no. 5, May 1979. From klaus@sat.t.u-tokyo.ac.jp Fri Jul 28 14:17:20 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 28 Jul 95 14:17:16 -0500; AA28906 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Fri, 28 Jul 95 14:17:13 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa14694; 27 Jul 95 19:14:33 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa14671; 27 Jul 95 18:49:56 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa19268; 27 Jul 95 18:49:15 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa10719; 27 Jul 95 12:51:54 EDT Received: from sat.t.u-tokyo.ac.jp by RI.CMU.EDU id aa19002; 27 Jul 95 12:50:37 EDT Received: by mail.sat.t.u-tokyo.ac.jp (8.6.12/3.4Wbeta6-SAT1.0) with SMTP id BAA20270; Fri, 28 Jul 1995 01:50:23 +0900 From: Klaus Mueller Received: by elf.sat.t.u-tokyo.ac.jp (4.1/sat-V0.6) id AA19714; Fri, 28 Jul 95 01:50:23 JST Date: Fri, 28 Jul 95 01:50:23 JST Message-Id: <9507271650.AA19714@elf.sat.t.u-tokyo.ac.jp> To: Connectionists@cs.cmu.edu Subject: new paper on learning curves FTP-host: archive.cis.ohio-state.edu FTP-file: pub/neuroprose/klaus.lcurve.ps.Z The following paper is now available for copying from the Neuroprose repository: klaus.lcurve.ps.Z klaus.lcurve.ps.Z (129075 bytes) 26 pages. M\"uller, K.-R., Murata, N., Finke, M., Schulten, K., Amari, S.: A Numerical Study on Learning Curves in Stochastic Multi-Layer Feed-Forward Networks The universal asymptotic scaling laws proposed by Amari et al. are studied in large scale simulations using a CM5. Small stochastic multi-layer feed-forward networks trained with back-propagation are investigated. In the range of a large number of training patterns $t$, the asymptotic generalization error scales as $1/t$ as predicted. For a medium range $t$ a faster $1/t^2$ scaling is observed. This effect is explained by using higher order corrections of the likelihood expansion. It is shown for small $t$ that the scaling law changes drastically, when the network undergoes a transition from ineffective to effective learning. (University of Tokyo Technical Report METR 03-95 and submitted) * NO HARDCOPIES * Best regards, Klaus &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& Dr. Klaus-Robert M\"uller C/o Prof. Dr. S. Amari Department of Mathematical Engineering University of Tokyo 7-3-1 Hongo, Bunkyo-ku Tokyo 113 , Japan mail: klaus@sat.t.u-tokyo.ac.jp Fax: +81 - 3 - 5689 5752 &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& PERMANENT ADRESS: &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& Dr. Klaus-Robert M\"uller GMD First (Gesellschaft f. Mathematik und Datenverarbeitung) Rudower Chaussee 5, 12489 Berlin Germany &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& From klaus@prosun.first.gmd.de Fri Jul 28 14:17:24 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 28 Jul 95 14:17:22 -0500; AA28914 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Fri, 28 Jul 95 14:17:19 -0500 Received: by TELNET-1.SRV.CS.CMU.EDU id aa16306; 28 Jul 95 13:29:50 EDT Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa16278; 28 Jul 95 13:16:46 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa16275; 28 Jul 95 13:01:51 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00598; 28 Jul 95 13:01:39 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa26546; 28 Jul 95 6:18:43 EDT Received: from prosun.first.gmd.de by CS.CMU.EDU id aa02738; 28 Jul 95 6:17:46 EDT Received: from lanke.first.gmd.de by prosun.first.gmd.de (4.1/SMI-4.1) id AA26435; Fri, 28 Jul 95 12:17:31 +0200 Received: from localhost by lanke.first.gmd.de (4.1/SMI-4.1) id AA01180; Fri, 28 Jul 95 12:17:26 +0200 Message-Id: <9507281017.AA01180@lanke.first.gmd.de> To: Connectionists@cs.cmu.edu Subject: new paper on "Analysis of Switching Dynamical Systems" Date: Fri, 28 Jul 95 12:17:24 +0200 From: klaus@prosun.first.gmd.de FTP-host: archive.cis.ohio-state.edu FTP-file: pub/neuroprose/pawelzik.switch.ps.Z FTP-file: pub/neuroprose/mueller.switch_speech.ps.Z The following 2 papers are now available for copying from the Neuroprose repository: pawelzik.switch.ps.Z, mueller.switch_speech.ps.Z pawelzik.switch.ps.Z (124459 bytes) 16 pages. Pawelzik, K., Kohlmorgen, J., M\"uller, K.-R.: Annealed Competition of Experts for a Segmentation and Classification of Switching Dynamics We present a method for the unsupervised segmentation of data streams originating from different unknown sources which alternate in time. We use an architecture consisting of competing neural networks. Memory is included in order to resolve ambiguities of input-output relations. In order to obtain maximal specialization, the competition is adiabatically increased during training. Our method achieves almost perfect identification and segmentation in the case of switching chaotic dynamics where input manifolds overlap and input-output relations are ambiguous. Only a small dataset is needed for the training proceedure. Applications to time series from complex systems demonstrate the potential relevance of our approach for time series analysis and short-term prediction. (Neural Computation in Press). mueller.switch_speech.ps.Z (427948 bytes) 11 pages. M\"uller, K.-R., Kohlmorgen, J., Pawelzik, K.: Analysis of Switching Dynamics with Competing Neural Networks, We present a framework for the unsupervised segmentation of time series. It applies to non-stationary signals originating from different dynamical systems which alternate in time, a phenomenon which appears in many natural systems. In our approach, predictors compete for data points of a given time series. We combine competition and evolutionary inertia to a learning rule. Under this learning rule the system evolves such that the predictors, which finally survive, unambiguously identify the underlying processes. Applications to time series from complex systems and speech are presented. The segmentation achieved is very precise and transients are included, a fact, which makes our approach promising for several applications. (IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences in Press). * NO HARDCOPIES * Best regards, Klaus &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& Dr. Klaus-Robert M\"uller C/o Prof. Dr. S. Amari Department of Mathematical Engineering University of Tokyo 7-3-1 Hongo, Bunkyo-ku Tokyo 113 , Japan mail: klaus@sat.t.u-tokyo.ac.jp Fax: +81 - 3 - 5689 5752 &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& PERMANENT ADRESS: &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& Dr. Klaus-Robert M\"uller GMD First (Gesellschaft f. Mathematik und Datenverarbeitung) Rudower Chaussee 5, 12489 Berlin Germany &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& From alisonw@cogs.susx.ac.uk Fri Jul 28 14:17:27 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 28 Jul 95 14:17:20 -0500; AA28912 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Fri, 28 Jul 95 14:17:16 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab16290; 28 Jul 95 13:27:23 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab16282; 28 Jul 95 13:03:06 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00609; 28 Jul 95 13:02:20 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa28314; 28 Jul 95 9:09:54 EDT Received: from rsuna-gw.susx.ac.uk by EDRC.CMU.EDU id aa08995; 28 Jul 95 9:09:39 EDT Received: by rsuna.crn.cogs.susx.ac.uk (Smail3.1.29.1 #3) id m0sbp9B-0006OUC; Fri, 28 Jul 95 14:08 BST Message-Id: Date: Fri, 28 Jul 95 14:08 BST From: Alison White To: connectionists@cs.cmu.edu, epsynet@uhupvm1.bitnet, info@aaai.org, neuron-request@CATTELL20.psych.upenn.edu, nick@zermatt.lcs.mit.edu, nl-kr@snyside1.sunnyside.com, nl-kr@cs.rochester.edu, nl-kr@cs.rpi.edu, ontology@pdadr1.pd.cnr.it Subject: AISB96 Call for Workshop Proposals Content-Length: 6325 ------------------------------------ AISB-96: CALL FOR WORKSHOP PROPOSALS ------------------------------------ Call for Workshop Proposals: AISB-96 University of Sussex, Brighton, England April 1 -- 2, 1996 Society for the Study of Artificial Intelligence and Simulation of Behaviour (SSAISB) Workshop Series Chair: Dave Cliff, University of Sussex Local Organisation Chair: Alison White, University of Sussex The AISB is the UK's largest and foremost Artificial Intelligence society -- now in it's 32nd year. The Society has an international membership of nearly 900 drawn from both academia and industry. Membership is open to anyone with interests in Artifical Intelligence and the Cognitive and Computing Sciences. The AISB Committee invites proposals for workshops to be held at the University of Sussex campus, on April 1st and 2nd, 1996. The AISB workshop series is held in even years during the Easter vacation. In odd years workshops are held immediately before the biennial conference. The intention of holding a regular workshop series is to provide an administrative and organisational framework for workshop organisers, thus reducing the administrative burden for individuals and freeing them to focus on the scientific programme. Accommodation, food, and social events are organised for all workshop participants by the local organisers. Proposals are invited for workshops relating to any aspect of Artificial Intelligence or the Simulation of Behaviour. Proposals, from an individual or a pair of organisers, for workshops between 0.5 and 2 days long will be considered. Workshops will probably address topics which are at the forefront of research, but perhaps not yet sufficiently developed to warrant a full-scale conference. In addition to research workshops, a 'Postgraduate Workshop' has become a successful regular event over recent years. This event focuses on how to survive the process of studying for a PhD in AI/Cognitive Science, and has a hybrid workshop/tutorial nature. We welcome proposals, particularly from current PhD survivors, to organise the 1996 Postgraduate Workshop at Sussex. For further information on organising the postgraduate workshop, please see the AISB96 web page (address below) or contact Dave Cliff or Alison White. Proposals for tutorials will also be considered, and will be assessed on individual merit: please contact Dave Cliff or Alison White for further details of submission of tutorial proposals. It is the general policy of AISB to only approve tutorials which look likely to be financially viable. Submission: ---------- A workshop proposal should contain the following information: 1. Workshop Title 2. A detailed outline of the workshop. This should include the necessary background and the potential target audience for the workshop and a justified estimate of the number of possible attendees. Please also state the length and preferred date(s) of the workshop. Specify any equipment requirements, indicating whether the organisers would be expected to meet them. 3. A brief resume of the organiser(s). This should include: background in the research area, references to published work in the topic area and relevant experience, such as previous organisation or chairing of workshops. 4. Administrative information. This should include: name, mailing address, phone number, fax, and email address if available. In the case of multiple organisers, information for each organiser should be provided, but one organiser should be identified as the principal contact. 5. A draft Call for Participation. This should serve the dual purposes of informing and attracting potential participants. The organisers of accepted workshops are responsible for issuing a call for participation, reviewing requests to participate and scheduling the workshop activities within the constraints set by the Workshop Organiser. They are also responsible for submitting a collated set of papers for their workshop to the Workshop Series Chair. Workshop participants will receive bound photocopies of the collated set of papers, with copyright retained by the authors. Individual workshop organisers may wish to approach publishers to discuss publication of workshop papers in journal or book forms. DATES: ------ Intentions to organise a workshop should be made known to the Workshop Series Chair (Dave Cliff) as soon as possible. Proposals must be received by October 1st 1995. Workshop organisers will be notified by October 15th 1995. Organisers should be prepared to send out calls for workshop participation as soon as possible after this date. Collated sets of papers to be received by March 15th 1996. Proposals should be sent to: Dave Cliff AISB96 Workshop Series Chair School of Cognitive and Computing Sciences University of Sussex Brighton BN1 9QH U.K. email: davec@cogs.susx.ac.uk phone: +44 1273 678754 fax: +44 1273 671320 Electronic submission (plain ascii text) is highly preferred, but hard copy submission is also accepted, in which case 5 copies should be submitted. Proposals should not exceed 2 sides of A4 (i.e. 120 lines of text approx.). General enquiries should be addressed to: Alison White AISB96 Local Organisation Chair School of Cognitive and Computing Sciences University of Sussex Brighton BN1 9QH U.K. email: alisonw@cogs.susx.ac.uk phone: +44 1273 678448 fax: +44 1273 671320 A copy of this call, with further details for workshop organisers (including a full schedule), is available on the WWW from: http://www.cogs.susx.ac.uk/aisb/aisb96/cfw.html A plain-ASCII version of the web page is available via anonymous ftp from: % ftp ftp.cogs.susx.ac.uk login: anonymous password: [your_email@your_address] ftp cd pub/aisb/aisb96 ftp get [filename]* ftp quit * Files available at present are: README call_for_proposals From pazzani@super-pan.ICS.UCI.EDU Fri Jul 28 18:53:02 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 28 Jul 95 18:52:53 -0500; AA01902 Received: from paris.ics.uci.edu by lucy.cs.wisc.edu; Fri, 28 Jul 95 18:52:39 -0500 Received: from super-pan.ics.uci.edu by paris.ics.uci.edu id aa10160; 28 Jul 95 11:49 PDT To: ML-LIST:; Subject: Machine Learning List: Vol. 7, No. 13 Reply-To: ml@ics.uci.edu Date: Fri, 28 Jul 1995 11:31:45 -0700 From: Michael Pazzani Message-Id: <9507281149.aa10160@paris.ics.uci.edu> Machine Learning List: Vol. 7, No. 13 Friday, July 28, 1995 Contents: Web information sources on Bayesian/Probabilistic networks WWW page for NASA data sets ML Repository Additions CFP: AIJ special issue LEARNING to PLAY GAMES job openings in data analysis/database mining PhD Studentships EP96 Change in Tech Chairs special MLJ issue 11th Conference on Uncertainty in AI, August 1995 Postdoc Positions in Hong Kong IPMU'96 Call for Paper JUNIOR SCIENTIST FELLOWSHIPS IEEE SMC Transactions: Special Issue on Autonomous Learning Robots EPIA'95: preliminary program 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 FTP'd from ics.uci.edu in pub/ml-list/V/ or N.Z where X and N are the volume and number of the issue; ID: anonymous PASSWORD: URL- http://www.ics.uci.edu/AI/ML/Machine-Learning.html ---------------------------------------------------------------------- From: Wray Buntine Subject: Web information sources on Bayesian/Probabilistic networks Date: Mon, 17 Jul 95 12:05:38 PDT Those who found David Heckerman's presentation and tutorial on learning Bayesian networks (at the recent IMLC'95) interesting should check out the following: * An up todate review of the state of the art in learning probabilistic networks can be found at: http://www.Heuristicrat.COM/wray/graphbib.ps.Z (this has been revised several times from a quick and dirty report distributed a year ago). Currently under review at a major journal. Some very nice work exists in this area. * Other tutorial articles on probabilistic networks by the UAI community are listed at: http://www.heuristicrat.com/wray/uaiconnections.html This includes a pointer to David Heckerman's tutorial article (a Microsoft report) that matches part of his talk. * Some of the techniques described by David were first applied to learning class probability trees (CART/C4.5 etc) way back in 1990. These Bayesian tree classification methods are available in IND2.1 as Bayesian Smoothing and Option Trees, and independent studies reported in Statlog (Spiegelhalter, Michie and Taylor, 1994) show the methods are highly competitive with CART and C4.5. Look for my trees paper in: http://www.Heuristicrat.COM/wray/refs.html#papers Jon Oliver presented a better variation of smoothing at IMLC'95. * Michael Jordan presented a paper showing technology transfer in the reverse direction: a probabilistic network algorithm adapted to do multivariate splits in trees (IMLC'93). The parallel between learning decision trees and learning Bayesian networks is remarkable. Techniques for learning class probability trees transfer easily to Bayesian networks and back. For instance, I mention in the review above how Usama Fayyad's discretization methods could well be adapted for learning Bayesian networks. I believe this is an excellent demonstration that the business of constructing a learning algorithm for a particular knowledge represention is something we now have well in hand, i.e., its becoming an engineering problem rather than research. In fact, several groups have already built compilers that take a problem represention and generate a learning algorithm. Remarkable but true! I gave some examples in my IMLC'95 tutorial, and the slides are available from: http://www.Heuristicrat.COM/wray/refs.html#tutes Of course, more realistically, we'd expect this kind of technology to create pieces of a learning algorithm rather than the whole thing, but nevertheless, expect in the near future to be able to prototype many learning algorithms faster. The technology exists to do this already. Wray Buntine +1 (510) 845-5810 [voice] Heuristicrats Research, Inc. +1 (510) 845-4405 [fax] 1678 Shattuck Avenue, Suite 310 wray@Heuristicrat.COM Berkeley, CA 94709-1631 http://WWW.Heuristicrat.COM/wray/ ------------------------------ Date: Mon, 17 Jul 95 09:12:05 PDT From: pjs@aig.jpl.nasa.gov (Padhraic J. Smyth) Subject: WWW page for NASA data sets The National Space Science Data Center (NSSDC) now has a WWW homepage with a significant amount of information about all of NASA's data sets from planetary exploration, space and solar physics, life sciences, astrophysics, including many links to other sites. This is probably the most useful place to start for people interested in data mining of NASA's vast scientific data sets. The address is: http://nssdc.gsfc.nasa.gov ------------------------------ From: "Patrick M. Murphy" Subject: ML Repository Additions Date: Thu, 20 Jul 1995 23:28:55 -0700 The following is a list of databases, etc. that have recently been added to the UCI Machine Learning Repository. Any comments or donations would be greatly appreciated (ml-repository@ics.uci.edu). Patrick M. Murphy (Librarian) P.S. Check out our new repository home page: http://www.ics.uci.edu/~mlearn/MLRepository.html - Bach Chorales (time-series) database (donated by Darrell Conklin) Sequential (time-series) domain. Single-line melodies of 100 Bach chorales (originally 4 voices). Number of Instances: 100 Chorales, each with ~45 events. Number of Attributes: 6 (nominal) per event. Includes grammar describing the chorale dataset. - Page Blocks Classification database (donated by Donato Malerba) The problem consists in classifying all the blocks of the page layout of a document that has been detected by a segmentation process. This is an essential step in document analysisin order to separate text from graphic areas. Indeed, the five classes are: text (1), horizontal line (2), picture (3), vertical line (4) and graphic (5). 5473 examples comes from 54 distinct documents. All attributes are numeric. - converter.lisp (donated by Stefanos Manganaris) This code reads UCI and C4.5 data files directly into LISP. Instances are transformed into any form, as specified by a user-defined LISP function. One typically has one such function for each learner. Functions can also be written to extract features or otherwise manipulate the data. (in utilities/) ------------------------------ From: Raul Valdes-Perez Subject: CFP: AIJ special issue Date: Fri, 7 Jul 95 16:13:03 EDT CALL FOR PAPERS ARTIFICIAL INTELLIGENCE Special Journal Issue on Scientific Discovery Editors: Herbert Simon (Carnegie Mellon) Derek Sleeman (Aberdeen) Raul Valdes-Perez (Carnegie Mellon) Advisory Editors: Bruce Buchanan (Pittsburgh), Lindley Darden (Maryland), Gerd Grasshoff (Hamburg), Pat Langley (ISLE & Stanford), Jan Zytkow (Wichita State) Submissions: Nov 1, 1995 Appearance: Scheduled for early 1997 In recent years, a substantial number of programs have been built and studied that perform nonroutine tasks in scientific discovery. Work on machine discovery is aimed at exploring and enlarging the scope of computing within science (scientific inference). Many of us believe that the potential for computers in this domain is very extensive, but there are also rational skeptics. An excellent way to resolve this issue is to produce programs that perform scientific work competently, and to characterize these programs in terms of general architectural features. A recent AAAI Spring Symposium on scientific discovery included both types of contributions. We seek submissions that address these fundamental issues, especially descriptions of working programs that achieve some form of creativity. Such programs may, for example, analyze data to discover descriptive or explanatory laws, conduct laboratory procedures automatically, plan experiments and experimental strategies, design instruments and research procedures, discover or revise appropriate problem representations, search for relevant data, draw inferences and make predictions from existing theories. That is, they participate in the numerous activities that are involved in scientific discovery. (Programs that perform in areas where computers are already main players are only relevant for this special issue, if they display the sort of creativity listed above.) Other appropriate submissions, not based on the description of a new program, might draw on the accumulated experience already reported in the literature to make more general statements about the scope of computing in science, about how best to extend its scope, or how to enhance existing programs. Such submissions, while more theoretical, should be based on the properties of working programs, should be rooted in empirical evidence, and should bear on scientific practice. All submissions should discuss the basic AI techniques which they have used in the course of building their Discovery System. Given the maturity of the Scientific Discovery field, we would not expect to publish, in this special issue, papers whose basic approach is regression analysis or simple curve fitting. Where all this may lead was foreseen by Allen Newell [quoted by D.G. Bobrow and P.J. Hayes in "Artificial Intelligence - Where Are We?" Artif.Intell.; 25(3), 1985]: We should, by the way, be prepared for some radical, and perhaps surprising, transformations of the disciplinary structure of science (technology included) as information processing pervades it. In particular, as we become more aware of the detailed information processes that go on in doing science, the sciences will find themselves increasingly taking a metaposition, in which doing science (observing, experimenting, theorizing, testing, archiving, ...) will involve understanding these information processes, and building systems that do the object-level science. Then the boundaries between the enterprise of science as a whole (the acquisition and organization of the knowledge of the world) and AI (the understanding of how knowledge is acquired and organized) will become increasingly fuzzy. If you intend to make a submission, please send a brief description well before the deadline to Raul Valdes-Perez (Computer Science Department; Carnegie Mellon University; Pittsburgh, PA 15213; USA). Email to valdes@cs.cmu.edu is preferred. ------------------------------ From: "Dean P. Foster" Subject: LEARNING to PLAY GAMES Date: Thu, 6 Jul 1995 10:56:06 -0400 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % I I A S A % % % % announces the First Tournament of % % % % LEARNING to PLAY GAMES % % % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Last year the Nobel Prize in economics was awarded for the concept of ``equilibrium'' in a game. An unresolved issue is how people actually learn to play games and whether some learning rules do better than others on average. The goal of this tournament is to advance our thinking on this issue. Contestants should submit a learning rule and (optionally) a game on which every contestant's rule may be tested. The collection of submitted rules will be treated as a population of organisms which evolve through natural selection over time. Pairs of rules are selected to play each game. The relative frequency of each rule grows in proportion to its past success and the winning rules for a particular game are those that have the highest frequency in the population after many generations. The deadline for submissions is November 1st, 1995. For the rules of the tournament send an email to tournamentinfo@iiasa.ac.at or point your World Wide Web brouser at http://www.iiasa.ac.at/welcome.html To have questions answered send email to tournament@iiasa.ac.at %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % What is IIASA % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% The International Institute for Applied Systems Analysis (IIASA), based in Laxenburg Austria, is an interdisciplinary, non-governmental research organization sponsored by the National Member Organizations of 17 nations. IIASA's current research program focuses on three central themes: Global Environmental Change; Global Economic and Technological Transitions; Systems Methods for the Analysis of Global Issues. The institute also conducts basic research in a variety of subjects including dynamical systems theory, optimization, game theory and decision analysis. ------------------------------ From: Scott Dixon Subject: job openings in data analysis/database mining Date: Tue, 11 Jul 1995 12:06:22 -0400 We have several openings in our computational chemistry group which might be of interest to readers of this list. Note in particular the jobs in database mining and in protein structure prediction which might be appropriate for someone with a background in machine learning as applied in these areas. OPPORTUNITIES IN COMPUTATIONAL CHEMISTRY/MOLECULAR MODELING SmithKline Beecham, a worldwide leader in pharmaceutical research has a number of openings in our Physical & Structural Chemistry Department. Scientific Programmer As a member of an established group, the selected candidate will assist in the development of state-of-the-art software. Qualifications include BS/MS in computer science or electrical engineering (with experience or course work in chemistry) or BS/MS in chemistry with demonstrated abilities in scientific computer programming. Excellent programming skills and knowledge of UNIX, C and FORTRAN are needed. Experience with Silicon Graphics workstations and computational chemistry software are desirable. Refer to Job Code #H0117. Protein Modeling This individual will be responsible for the development and application of methods to assign structure and function to genome sequence information. Qualifications required include a Ph.D. in chemistry, biophysics or bioinformatics with extensive experience in biopolymer sequence analysis and protein modeling. Other requirements include excellent computer skills and the ability to develop computer programs and new algorithms. A knowledge of DNA sequencing methods and molecular biology is desirable. Refer to Job Code #H0118. Combinatorial Chemistry/ Molecular Diversity The selected individual will join with other team members to develop and apply methods for the design of combinatorial chemical libraries and the analysis of diversity in chemical databases. The necessary qualifications include a Ph.D. in chemistry or a related field and extensive experience in computational chemistry. Excellent computer skills and communication skills are also necessary. Experience in pattern recognition or chemical diversity methods is desirable. Job Code #H00M. Database Mining The appropriate individual will have a Ph.D. in chemistry or biochemistry or computer science (or related field) with extensive experience in pattern recognition, machine learning or chemometrics. Excellent communication and computer skills, including the ability to develop new algorithms, are required. Experience in chemical or biological database analysis is desirable. Job Code #H00L. Located in our state-of-the-art research facility in suburban Philadelphia, SmithKline Beecham offers an excellent compensation/benefits/relocation package. Interested candidates should send resume with salary requirements indicating desired Job Code, to: SmithKline Beecham Pharmaceuticals, Job Code ____ P.O. Box 2645 Bala Cynwyd, PA 19004. We are an Equal Opportunity Employer, M/F/D/V. ------------------------------ From: R.Poli@cs.bham.ac.uk Subject: PhD Studentships Date: Mon, 17 Jul 95 18:28:44 BST The University of Birmingham School of Computer Science Research Studentships in ~~~~~~~~ ~~~~~~~~~~~~ EMERGENT AND EVOLUTIONARY BEHAVIOUR, INTELLIGENCE, AND COMPUTATION (EEBIC) Applications are invited for a number of Studentships for full-time PhD research in the School of Computer Science to carry out research within the recently founded EEBIC group. The group's research interests include: evolutionary computation (e.g. genetic algorithms and genetic programming), emergent behaviour, emergent intelligence (e.g. emergent communication), emergent computation and artificial life and their practical applications in hard engineering problems. The members of the group, at Birmingham and elsewhere, are active researchers in Artificial Intelligence, Engineering or Psychology with a variety of different backgrounds including Biology, Computer Science, Engineering, Psychology and Philosophy. In addition to EEBIC, the research experience of the members of the group includes computer vision, neural nets, signal processing, intelligent autonomous agents, hybrid inference systems, computer emotions, logic and many others. The group interacts very closely with the Cognition and Affect group led by Aaron Sloman who is a member of both groups. (For more information see URLs: ftp://ftp.cs.bham.ac.uk/pub/groups/cog_affect and http://www.cs.bham.ac.uk/~axs .) The successful applicants will join the group's effort to explore EEBIC in many interesting directions (from engineering to psychology, from new practical applications to new theoretical frameworks). They will have constant interaction and collaboration with the other members of the group. In addition to the usual requirements of possessing a good honours degree (equivalent to a first or upper second class degree in a UK university) and being EU residents, the successful candidates will need to be particularly open minded to the cross-fertilisation in the group deriving from the different backgrounds and experience of the members. Additional information about how to apply and about the School is available via WWW from URL: http://www.cs.bham.ac.uk Informal enquiries about the EEBIC group can be directed to Riccardo Poli Phone: +44-121-414-3739 Fax: +44-121-414-4281 Email: R.Poli@cs.bham.ac.uk Enquiries concerning the Cognition and Affect group may be sent to Aaron Sloman Phone: +44-121-414-4775 Fax: +44-121-414-4281 Email: A.Sloman@cs.bham.ac.uk For any other queries contact our research students' admission tutor: Dr Peter Hancox Email: P.J.Hancox@cs.bham.ac.uk ------------------------------ From: "Peter J. Angeline" Subject: EP96 Change in Tech Chairs Date: Thu, 13 Jul 1995 13:45:04 -0400 EP96 had a minor reorgnization. Please note that the addresses for sending submissions to the conference are down to 2 now! Submissions are due to one of the technical chairs by September 26th. EP96 The Fifth Annual Conference On Evolutionary Programming February 29 to March 3, 1996 Sheraton Harbor Island Hotel San Diego, CA, USA Sponsored by The Evolutionary Programming Society The Fifth Annual Conference on Evolutionary Programming will serve as a forum for researchers investigating applications and theory of evolutionary programming and other related areas in evolutionary and natural computation. Topics of interest include but are not limited to the use of evolutionary simulations in optimization, neural network training and design, automatic control, image processing, and other applications, as well as mathematical theory or empirical analysis providing insight into the behavior of such algorithms. Of particular interest are applications of simulated evolution to problems in biology. Conference Committee General Chairman: Lawrence J. Fogel, Natural Selection, Inc. Technical Program Co-Chairs: Peter J. Angeline, Loral Federal Systems Thomas Baeck, Informatik Centrum Dortmund Finance Chair: V. William Porto, Orincon Corporation Local Arrangements: Ward Page, Naval Command Control and Ocean Surveillance Center Conference World Wide Web Page: http://www.aic.nrl.navy.mil/galist/EP96/ Submission Information Authors are invited to submit papers which describe original unpublished research in evolutionary programming, evolution strategies, genetic algorithms and genetic programming, artificial life, cultural algorithms, and other models that rely on evolutionary principles. Specific topics include but are not limited to the use of evolutionary simulations in optimization, neural network training and design, automatic control, image processing, and other applications, as well as mathematical theory or empirical analysis providing insight into the behavior of such algorithms. Of particular interest are applications of simulated evolution to problems in biology. Hardcopies of manuscripts must be received by one of the technical program co-chairs by September 26, 1995. Electronic submissions cannot be accepted. Papers should be clear, concise, and written in English. Papers received after the deadline will be handled on a time- and space-available basis. The notification of the program committee's review decision will be mailed by November 30, 1995. Papers eligible for the student award must be marked appropriately for consideration (see below). Camera ready papers are due at the conference, and will be published shortly after its completion. Submissions should be single-spaced, 12 pt. font and should not exceed 15 pages including figures and references. Send five (5) copies of the complete paper to: In Europe: Thomas Baeck Informatik Centrum Dortmund Joseph-von-Fraunhofer-Str. 20 D-44227 Dortmund Germany Email: baeck@home.informatik.uni-dortmund.de In US: Peter J. Angeline Loral Federal Systems 1801 State Route 17C Mail Drop 0210 Owego, NY 13827 Email: pja@lfs.loral.com Authors outside Europe or the United States may send their paper to any of the above technical chairmen at their convenience. Evolutionary Programming Society Award for Best Student Paper In order to foster student contributions and encourage exceptional scholarship in evolutionary programming and closely related fields, the Evolutionary Programming Society awards one exceptional student paper submitted to the Annual Conference on Evolutionary Programming. The award carries a $500 cash prize and a plaque signifying the honor. To be eligible for the award, all authors of the paper must be full-time students at an accredited college, university or other educational institution. Submissions to be considered for this award must be clearly marked at the top of the title page with the phrase "CONSIDER FOR STUDENT AWARD." In addition, the paper should be accompanied by a cover letter stating that (1) the paper is to be considered for the student award (2) all authors are currently enrolled full-time students at a university, college or other educational institution, and (3) that the student authors are responsible for the work presented. Only papers submitted to the conference and marked as indicated will be considered for the award. Late submissions will not be considered. Officers of the Evolutionary Programming Society, students under their immediate supervision, and their immediate family members are not eligible. Judging will be made by officers of the Evolutionary Programming Society or by an Awards Committee appointed by the president. Judging will be based on the perceived technical merit of the student's research to the field of evolutionary programming, and more broadly to the understanding of self-organizing systems. The Evolutionary Programming Society and/or the Awards Committee reserves the right not to give an award in any year if no eligible student paper is deemed to be of award quality. Presentation of the Student Paper Award will be made at the conference. Important Dates --------------- September 26, 1995 - Submission deadline for papers November 30, 1995 - Notification sent to authors February 29, 1996 - Conference Begins ------------------------------ Date: Wed, 26 Jul 95 15:14:05 EDT From: gordon@aic.nrl.navy.mil Subject: special MLJ issue The upcoming July/August issue of Machine Learning journal is a special issue on "Bias Evaluation and Selection." We understand there's a tendency when a special issue appears to put the issue aside and not read it if the topic is not in your area of specialty within machine learning. Nevertheless, we believe the topic of bias is relevant to all forms of machine learning. The issue begins with an introductory article that formalizes the definitions of representational and procedural bias. It then presents a framework for bias shifting. Although the introductory article is expressed in terms of supervised concept learning, the definitions and framework should be easily extendible to any type of learning. The remainder of the issue consists of articles about biases in different types of learning (supervised concept learning, ILP, speedup learning). One lesson our community has learned from the No Free Lunch theorems (Conservation Law) is a reminder of the importance of delineating regions of expertise/weakness, i.e., regions of problem space for which our algorithm or bias is well/poorly suited. We believe the articles in this issue take an important step in addressing this task. We hope this issue will: 1) provide interesting and informative reading, 2) encourage people in other areas of machine learning not represented in this issue (e.g., reinforcement learning, cognitive learning, evolutionary computation) to apply the definitions and methodologies presented in this issue to their areas of expertise, and 3) encourage further research on bias and other unifying themes that are of central concern to all of machine learning (e.g., Tom Dietterich's ML95 paper on unifying EBL and RL is a similar step in this direction). Diana Gordon Marie desJardins Editors ------------------------------ From: David Poole Subject: 11th Conference on Uncertainty in AI, August 1995 Date: Fri, 21 Jul 1995 10:01:53 UTC-0700 The Conferences in Uncertianty in AI are the premier forum for work on reasoning under uncertainty (including probabilistic and other formalisms for uncertainty, representations for uncertainty (such as Bayesian networks), algorithms for inference under uncertainty and learning under uncertainty). The 11th Conference on Uncertianty in AI will be held in Montreal, 18-20 August 1995 (just before IJCAI-95). For full details including registration information and an online proceedings see the URL: http://www.cs.ubc.ca/spider/poole/UAI95.html The program for UAI-95 is as follows: UAI-95 - 11th Conference on Uncertainty in AI McGill University, Montreal, Quebec, 18-20 August 1995 =================================== Final Program =================================== ============================== Friday 18 August Overview ============================== 08:45 -- 09:00 Opening remarks 09:00 -- 10:15 Invited talk #1 (Haussler) 10:15 -- 10:30 Break 10:30 -- 12:30 Presentation session #1 12:30 -- 14:00 Lunch 14:00 -- 16:00 Poster session #1 16:00 -- 16:15 Break 16:30 -- 18:30 Presentation session #2 ================================ Saturday 19 August Overview ================================ 09:00 -- 10:30 Invited talk #2 (Jordan) + panel discussion 10:30 -- 10:45 Break 10:45 -- 12:45 Presentation session #3 12:45 -- 14:30 Lunch 14:30 -- 16:00 Invited talk #3 (Subrahmanian) 16:00 -- 16:15 Break 16:15 -- 18:15 Presentation session #4 ================================ Sunday 20 August Overview ================================ 09:00 -- 10:30 Invited talk #4 (Shafer) + panel discussion 10:30 -- 10:45 Break 10:45 -- 12:45 Presentation session #5 12:45 -- 14:30 Lunch 14:30 -- 16:00 Poster session #2 16:00 -- 16:15 Break 16:15 -- 18:15 Presentation session #6 ============================================== Invited talks ============================================== #1 Haussler "Hidden Markov and Related Statistical Models: How They Have Been Applied to Biosequence Analysis" #2 Jordan (with panel on learning) "A Few Relevant Ideas from Statistics, Neural Networks, and Statistical Mechanics" #3 Subrahamanian "Uncertainty in Deductive Databases" #4 Shafer (with panel on causality) "The Multiple Causal Interpretation of Bayes Nets" ================================================= Presentation session #1 ================================================= Wellman/Ford/Larson PATH PLANNING UNDER TIME-DEPENDENT UNCERTAINTY Horvitz/Barry DISPLAY OF INFORMATION FOR TIME-CRITICAL DECISION MAKING Pearl/Robins PROBABILISTIC EVALUATION OF SEQUENTIAL PLANS FROM CAUSAL MODELS WITH HIDDEN VARIABLES Haddawy/Doan/Goodwin EFFICIENT DECISION-THEORETIC PLANNING: TECHNIQUES AND EMPIRICAL ANALYSIS Fargier/Lang/Clouaire/Schiex A CONSTRAINT SATISFACTION FRAMEWORK FOR DECISION UNDER UNCERTAINTY ================================================= Presentation session #2 ================================================= Xu/Smets GENERATING EXPLANATIONS FOR EVIDENTIAL REASONING ========> Best student paper <=========== Meek CAUSAL INFERENCE AND CAUSAL EXPLANATION WITH BACKGROUND KNOWLEDGE ========> Best student paper <=========== Cayrac/Dubois/Prade PRACTICAL MODEL-BASED DIAGNOSIS WITH QUALITATIVE POSSIBILISTIC UNCERTAINTY Srinivas/Horvitz EXPLOITING SYSTEM HIERARCHY TO COMPUTE REPAIR PLANS IN PROBABILISTIC MODEL-BASED DIAGNOSIS Balke/Pearl COUNTERFACTUALS AND POLICY ANALYSIS IN STRUCTURAL MODELS ================================================= Presentation session #3 ================================================= Jensen CAUTIOUS PROPAGATION IN BAYESIAN NETWORKS Darwiche STRONG CONDITIONING ALGORITHMS FOR EXACT AND APPROXIMATE INFERENCE IN CAUSAL NETWORKS ========> Best student paper <=========== Draper CLUSTERING WITHOUT (THINKING ABOUT) TRIANGULATION ========> Best student paper <=========== Goldszmidt FAST BELIEF UPDATE USING ORDER-OF-MAGNITUDE PROBABILITIES ========> Best student paper <=========== Harmanec TOWARD A CHARACTERIZATION OF UNCERTAINTY MEASURE FOR THE DEMPSTER-SHAFER THEORY ========> Best student paper <=========== ================================================= Presentation session #4 ================================================= Dubois/Prade NUMERICAL REPRESENTATION OF ACCEPTANCE Grosof TRANSFORMING PRIORITIZED DEFAULTS AND SPECIFICITY INTO PARALLEL DEFAULTS Weydert DEFAULTS AND INFINITESIMALS DEFEASIBLE INFERENCE BY NONARCHIMEDEAN ENTROPY-MAXIMIZATION Benferhat/Saffiotti/Smets BELIEF FUNCTIONS AND DEFAULT REASONING Ngo/Haddawy/Helwig A THEORETICAL FRAMEWORK FOR CONTEXT-SENSITIVE TEMPORAL PROBABILITY MODEL CONSTRUCTION WITH APPLICATION TO PLAN PROJECTION ========================================== Presentation session #5 ========================================== Campos/Moral INDEPENDENCE CONCEPTS FOR CONVEX SETS OF PROBABILITIES Geiger/Heckerman A CHARACTERIZATION OF THE DIRICHLET DISTRIBUTION THROUGH GLOBAL AND LOCAL INDEPENDENCE Spirtes DIRECTED CYCLIC GRAPHICAL REPRESENTATIONS OF FEEDBACK MODELS Pynadath/Wellman ACCOUNTING FOR CONTEXT IN PLAN RECOGNITION, WITH APPLICATION TO TRAFFIC MONITORING Srinivas MODELING FAILURE PRIORS AND PERSISTENCE IN MODEL-BASED DIAGNOSIS ========================================== Presentation session #6 ========================================== Poole EXPLOITING THE RULE STRUCTURE FOR DECISION MAKING WITHIN THE INDEPENDENT CHOICE LOGIC Krause/Fox/Judson IS THERE A ROLE FOR QUALITATIVE RISK ASSESSMENT? Srinivas POLYNOMIAL ALGORITHM FOR COMPUTING THE OPTIMAL REPAIR STRATEGY IN A SYSTEM WITH INDEPENDENT COMPONENT FAILURES Boldrin/Sossai AN ALGEBRAIC SEMANTICS FOR POSSIBILISTIC LOGIC Hajek/Godo/Esteva FUZZY LOGIC AND PROBABILITY ============================================================== Poster session #1 ============================================================== 1. Jack Breese, Russ Blake. AUTOMATING COMPUTER BOTTLENECK DETECTION WITH BELIEF NETS 2. Wray L. Buntine CHAIN GRAPHS FOR LEARNING 3. J.L. Castro, J.M. Zurita AN APPROACH TO GET THE STRUCTURE OF A FUZZY RULE UNDER UNCERTAINTY 4. Tom Chavez, Ross Shachter DECISION FLEXIBILITY 5. Arthur L. Delcher, Adam Grove, Simon Kasif, Judea Pearl LOGARITHMIC-TIME UPDATES AND QUERIES IN PROBABILISTIC NETWORKS 6. Eric Driver, Darryl Morrell CONTINUOUS BAYESIAN NETWORKS 7. Nir Friedman, Joseph Y. Halpern PLAUSIBILITY MEASURES: A USER'S GUIDE 8. David Galles, Judea Pearl TESTING IDENTIFIABILITY OF CAUSAL EFFECTS 9. Steve Hanks, David Madigan, Jonathan Gavrin PROBABILISTIC TEMPORAL REASONING WITH ENDOGENOUS CHANGE 10. David Heckerman BAYESIAN METHODS FOR LEARNING CAUSAL NETWORKS 11. Eric Horvitz, Adrian Klein STUDIES IN FLEXIBLE LOGICAL INFERENCE: A DECISION-MAKING PERSPECTIVE 12. George John, Pat Langley ESTIMATING CONTINUOUS DISTRIBUTIONS IN BAYESIAN CLASSIFIERS 13. Uffe Kjaerulff HUGS: COMBINING EXACT INFERENCE AND GIBBS SAMPLING IN JUNCTION TREES 14. Prakash P. Shenoy A NEW PRUNING METHOD FOR SOLVING DECISION TREES AND GAME TREES 15. Peter Spirtes, Christopher Meek, Thomas Richardson CAUSAL INFERENCE IN THE PRESENCE OF LATENT VARIABLES AND SELECTION BIAS 16. Nic Wilson AN ORDER OF MAGNITUDE CALCULUS 17. S.K.M. Wong, C.J. Butz, Y. Xiang A METHOD FOR IMPLEMENTING A PROBABILISTIC MODEL AS A RELATIONAL DATABASE
18. Y. Xiang OPTIMIZATION OF INTER-SUBNET BELIEF UPDATING IN MULTIPLY SECTIONED BAYESIAN NETWORKS 19. Nevin Lianwen Zhang INFERENCE WITH CAUSAL INDEPENDENCE IN THE CPSC NETWORK =============================================== Poster Session #2 =============================================== 1. Fahiem Bacchus, Adam Grove GRAPHICAL MODELS FOR PREFERENCE AND UTILITY 2. Enrique Castillo, Remco R. Bouckaert, Jose Maria Sarabia, ERROR ESTIMATION IN APPROXIMATE BAYESIAN BELIEF NETWORK INFERENCE 3. David Maxwell Chickering A NEW CHARACTERIZATION OF EQUIVALENT BAYESIAN NETWORK STRUCTURES 4. Marek J. Druzdzel, Linda C. van der Gaag ELICITATION OF PROBABILITIES: COMBINING QUALITATIVE AND QUANTITATIVE INFORMATION 5. Kazuo J. Ezawa, Til Schuermann LEARNING SYSTEM: A RARE BINARY OUTCOME WITH MIXED DATA STRUCTURES 6. David Heckerman, Dan Geiger LEARNING BAYESIAN NETWORKS: A UNIFICATION FOR DISCRETE AND GAUSSIAN DOMAINS 7. David Heckerman, Ross Shachter A DEFINITION AND GRAPHICAL REPRESENTATION FOR CAUSALITY 8. Mark Hulme IMPROVED SAMPLING FOR DIAGNOSTIC REASONING IN BAYESIAN NETWORK 9. Ali Jenzarli INFORMATION/RELEVANCE INFLUENCE DIAGRAMS 10. Keiji Kanazawa, Daphne Koller, Stuart Russell STOCHASTIC SIMULATION ALGORITHMS FOR DYNAMIC PROBABILISTIC NETWORKS 11. Grigoris I. Karakoulas PROBABILISTIC EXPLORATION IN PLANNING WHILE LEARNING 12. Alexander V. Kozlov, Jaswinder Pal Singh APPROXIMATE PROBABILISTIC INFERENCE IN BELIEF NETWORKS 13. Michael L. Littman, Thomas L. Dean, Leslie Pack Kaelbling ON THE COMPLEXITY OF SOLVING MARKOV DECISION PROBLEMS 14. Chris Meek STRONG-COMPLETENESS AND FAITHFULNESS IN BAYES NETWORKS 15. Simon Parsons REFINING REASONING IN QUALITATIVE PROBABILISTIC NETWORKS 16. Judea Pearl ON THE TESTABILITY OF CAUSAL MODELS WITH LATENT AND INSTRUMENTAL VARIABLES 17. Gregory Provan ABSTRACTION IN BELIEF NETWORKS: THE ROLE OF INTERMEDIATE STATES IN DIAGNOSTIC REASONING 18. Marco Valtorta, Young-Gyun Kim ON THE DETECTION OF CONFLICTS IN DIAGNOSTIC BAYESIAN NETWORKS USING ABSTRACTION David Poole, Office: +1 (604) 822-6254 Department of Computer Science, Fax: +1 (604) 822-5485 University of British Columbia, Email: poole@cs.ubc.ca 2366 Main Mall, URL: http://www.cs.ubc.ca/spider/poole Vancouver, B.C., Canada V6T 1Z4 FTP: ftp://ftp.cs.ubc.ca/ftp/local/poole ------------------------------ From: Christian Schunn Subject: Postdoc Positions in Hong Kong Date: Sat, 22 Jul 1995 14:13:03 -0400 (EDT) Post-Doctoral Fellowships in Cognitive Science, University of Hong Kong. The University of Hong Kong is offering some well-paid post-doctoral fellowships for next academic year, open to young academics who have completed and submitted their Ph.D. dissertations, and who wish to further their research here. In particular, we are keen to recruit highly motivated and energetic researchers in one of the fields of Cognitive Science. We have recently set up a Cognitive Science Centre at the University of Hong Kong, to support collaborative research in the area from amongst the many departments at this University that touch on this subject. This academic year will also see the first intake of students into a first degree programme in Cognitive Science, and there will be opportunities for the successful candidate(s) to contribute to the teaching on this course. The posts may be held for up to three years. The salary will be in the range HK$21,345 (US$2,737; GBP1,730) per month to HK$34,415 (US$4,412; GBP2,790) per month, depending on experience, and is incremental each year. The closing date for applications is 15th October, 1995. However, overseas applicants are advised to contact me earlier than this, to discuss research interests and practical details. Please pass this email on to your students or others who you think might be interested and qualified. John Spinks, Director, Cognitive Science Centre. spinks@hkucc.hku.hk ------------------------------ From: Congreso IPMU96 Subject: IPMU'96 Call for Paper Date: Thu, 20 Jul 95 14:08:27 +0100 ***************************************************** * Preliminary Call for Paper * * * * IPMU'96 * * * * Information Processing and Management of * * Uncertainty * * in Knowledge Based Systems * * * * Granada, Spain, July 1-5, 1996 * ***************************************************** ======================================================== Organized by Departamento de Ciencias de la Computacion e Inteligencia Artificial. Universidad de Granada. Sponsored by Junta de Andalucia. Universidad de Granada. Ayuntamiento de Granada. ======================================================== ======================================================== Aims and Scope ======================================================== Organized at a regular two-year interval, the IPMU International Conference deals with the difficulties existing in the acquisition, representation, management and transmission of data in knowledge-based and decision-making systems. It brings together researches working on various methodologies for the management of uncertain information and provides a useful exchange between theorists and practitioners using these different methodologies. ======================================================== Topics of particular interest ======================================================== * Uncertainty Methods: Measures of Information and Uncertainty, Bayesian and Probabilistic Methods, Fuzzy Methods, Mathematical Theory of Evidence, Belief Networks, Chaos Theory. * Non-standard Logics: Non-monotonic Logics, Approximate Reasoning, Multivalued Logics, Modal Logics, Temporal Reasoning, Case-based Reasoning. * Knowledge Acquisition and Representation: Machine Learning, Inductive Methods, Commonsense Knowledge, Intelligent Databases and Information Systems. * Intelligent Systems: Fuzzy Control, Neural Networks, Genetic Algorithms and Evolutionary Computation, Expert Systems under Uncertainty, Decision Support Systems, Multicriteria and Group Decision Making, Pattern Recognition, Image Processing, Classification, Belief Updating and Inconsistency Handling. ======================================================== Address and Location ======================================================== IPMU'96 Dpto. Ciencias de la Computacion e Inteligencia Artificial. E.T.S.I. Informatica. Avda. Andalucia, 38 Universidad de Granada. 18071 Granada. Spain. Phone: +34.58.244019 Fax: +34.58.243317 e-mail: ipmu96@robinson.ugr.es e-mail for submissions: ipmu96-submissions@robinson.ugr.es URL: http://pirata.ugr.es/ipmu96.html Granada, a world-famous city, whose history spans over thousand years, also has outstanding features as a modern conference town. The Alhambra, the city's monuments, cultural and University traditions, as well as excellent leisure facilities, good restaurants, lively night life, the Sierra Nevada mountains and the Coast, all attract thousand of visitors to Granada every year. ======================================================== Submission Information ======================================================== Authors should submit three copies of each full paper by November 1st. There will be a six page (two columns) limit on the final versions of accepted papers. Papers will be carefully reviewed and authors will be notified on the acceptance/rejection by February 1st, 1996. Final camera-ready copies for publication will required by April 1st, 1996. Submissions may be sent by mail to the address included in this call. Electronic submissions are encouraged. To submit a paper electronically, send an e-mail to ipmu96-submissions@robinson.ugr.es including the following information (in this order): a) Paper title (plain text) b) Author's names, including professional status. c) Surface mail and e-mail address for a contact author (plain text) d) A short abstract, including keywords or topic indicators (plain text) e) Paper body (Postscript format) Proceedings will be available at the opening of the Conference. Relevant papers may be selected for publication in special issues of leading international journals. ======================================================== Dates and Deadlines ======================================================== Nov. 1 1995: Deadline for submission of papers. Feb. 1 1996: Notification of acceptance/rejection. Apr. 1 1996: Reception of final camera-ready. May 15 1996: Deadline for early registration. July 1-5 1996: CONFERENCE. Early Registration Fee: 60.000 pesetas (ptas). Late Registration Fee: 70.000 pesetas (ptas). ======================================================== Invited sessions ======================================================== A number of invited sessions on special topics will be included in the program of IPMU'96. Authors will be invited to contribute to these sessions, which will be chaired by recognized experts in these topics. Proposals to organize invited sessions are welcome to be considered by the committee until September 15th. ======================================================== Honorary President ======================================================== Lotfi A. Zadeh(University of California, Berkeley, USA) ======================================================== General Chairpersons Committee ======================================================== Bernardette Bouchon-Meunier (CNRS, France) Miguel Delgado (University of Granada, Spain) Jose Luis Verdegay (University of Granada, Spain) Maria Amparo Vila (University of Granada, Spain) Ronald R. Yager (Iona College, NY, USA) ======================================================== International Program Committee ======================================================== J. Aczel (Canada) J. Aguilar-Martin (France) J. Baldwin (UK) S. Barro (Spain) A. Blanco (Spain) H. Berenji (USA) J. Bezdek(USA) P. Bonissone (USA) P. Bosc (France) J.L. Castro(Spain) D. Dubois (France) F. Esteva (Spain) M. Fedrizzi (Italy) M.A. Gil (Spain) A. Gonzalez (Spain) S. Guiasu (Canada) J. Gutierrez (Spain) F. Herrera (Spain) K. Hirota(Japan) J. Jacas (Spain) J.Y. Jaffray (France) J. Kacprzyk (Poland) A. Kandel (USA) E.P. Klement (Austria) G. Klir (USA) R. Kruse (Germany) M.T. Lamata (Spain) H.L. Larsen (Denmark) S.L. Lauritzen (Denmark) R. Lopez de Mantaras (Spain) R. Marin (Spain) J. Montero (Spain) S. Moral (Spain) H. Nguyen (USA) S. Ovchinnikov(USA) J. Pearl (USA) H. Prade(France) I. Requena (Spain) A. Rocha (Brazil) E. Ruspini (USA) A. Sage (USA) E. Sanchez (France) G. Shafer (USA) P. Shenoy (USA) P. Smets (Belgium) M. Sugeno (Japan) S. Termini (Italy) A. Titli (France) E. Trillas (Spain) I.B. Turksen (USA) R. Valle (France) L. Valverde (Spain) T. Yamakawa (Japan) H.J. Zimmermann (Germany) ======================================================== Organizing Committee: ======================================================== S. Moral (President) A. Blanco J.L. Castro J.C. Cubero A. Gonzalez F. Herrera M.T. Lamata J.M. Medina O. Pons I. Requena J.M. Zurita ======================================================== PRE-REGISTRATION FORM ======================================================== If you want to be kept informed, please fill in this form and return it to the address included in this call. ........................ cut here ....................... Pre-Registration Form Surname: First Name: Mailing Address: Phone: Fax: E-Mail: _ |_| I am interested in attending the conference. _ |_| I am interested in submitting a paper. ------------------------------ From: Peter Reimann Subject: JUNIOR SCIENTIST FELLOWSHIPS Date: Mon, 3 Jul 1995 14:12:50 +0000 CALL FOR APPLICATIONS: JUNIOR SCIENTIST FELLOWSHIPS IN THE RESEARCH PROGRAMME "LEARNING IN HUMANS AND MACHINES (LHM)" For the years 1996-1997, 20 Junior Scientists can participate as fellows in the LHM programme funded by the European Science Foundation, Strasbourg. A "Junior Scientist" to this programme is a researcher who is currently working on a learning research related Ph.D. or has completed it not more then four years ago. A fellowship allows to participate in one of the programme's five Task Forces and comprises mainly travel support; no other payments (such as a salary) are included. The programme is interdisciplinary (psychology, instructional science, machine learning) and fellowships can be given to scientists from all European countries (not restricted to EU nations). **Note: Only scientists working during the 2-year period in Europe (but not confined to EU nations) are eligible** If you want to apply for participation, please send in the following documents: Curriculum vitae, description of your Ph.D. project and list of publications (if available), a short description of the laboratory you are working in, a letter of recommendation, and a statement indicating of which Task Force you would like to be a member of and how your own research over the next two years could contribute to that Task Force's theme. In order to get more information about the Task Forces, consult the WWW pages starting at the URL http://www.di.unito.it/pub/WWW/lhm_programme/home.html. Alternatively, mail to esf-lhm-info@psychologie.uni-freiburg.de or write to the address given below. The documents should be sent by August 31, 1995, to: Dr Peter Reimann LHM Research Coordinator Universitaet Freiburg Psychologisches Institut Niemensstr. 10 D-79085 Freiburg. Fax: +49 761 2032490. Decisions concerning the fellowships will be made by October 31, 1995. ------------------------------ From: Marco Dorigo Subject: IEEE SMC Transactions: Special Issue on Autonomous Learning Robots Date: Tue, 11 Jul 95 20:07:49 +0200 The IEEE Transactions on Systems, Man, and Cybernetics will soon publish a Special Issue on Learning Autonomous Robots. I prepared a Mosaic (WWW) page containing the Editorial (in HTML format) and abstracts of the accepted papers. The page URL is: http://iridia.ulb.ac.be/dorigo/SI/Special_Issue.html Marco Dorigo, TSMC Guest Editor IRIDIA Universite' Libre de Bruxelles Avenue Franklin Roosvelt 50 CP 194/6 1050 Bruxelles, Belgium tel. +32-2-6503167 fax +32-2-6502715 mdorigo@ulb.ac.be http://iridia.ulb.ac.be/dorigo/dorigo.html ------------------------------ From: Nuno Joao Mamede Subject: EPIA'95: preliminary program Date: Mon, 10 Jul 95 21:48:30 +0100 EPIA'95 - PRELIMINARY PROGRAM SEVENTH PORTUGUESE CONFERENCE ON ARTIFICIAL INTELLIGENCE Casino Park Hotel, Funchal, Madeira Island, Portugal 3-6 October, 1995 (Under the auspices of the Portuguese Association for AI) The 7th Portuguese Conference on Artificial Intelligence will be held at Funchal, Madeira Island, Portugal, October 3-6, 1995. As in the past, EPIA 95 is an international conference with English as the official language. The conference covers all areas of Artificial Intelligence, including theoretical areas, foundational areas, and applications. The scientific program consists of invited lectures, tutorials, demonstrations and paper presentations. There will also be parallel workshops on Expert Systems, Fuzzy Logic and Neural Networks, and Applications of AI to Robotics and Vision Systems. ====================================================================== PRELIMINARY PROGRAM (Summary) ====================================================================== Tuesday - October, 3 95 ~~~~~~~~~~~~~~~~~~~~~~~ 9:00 - 12:30 TUTORIAL 1 - Artificial Life and Autonomous Robots Luc Steels 9:00 - 12:30 TUTORIAL 3 - Introduction to Artificial Intelligence Ernesto Costa (in Portuguese) 14:30 - 18:00 TUTORIAL 2 - Virtual Reality - The AI perspective David Hogg 14:30 - 18:00 TUTORIAL 4 - Design of Expert Systems Ernesto Morgado (in Portuguese) Wednsday - October, 4 95 ~~~~~~~~~~~~~~~~~~~~~~~~ 9:00 - 9:40 OPENING SESSION 9:40 - 10:30 QUALITATIVE REASONING 10:30 - 10:50 Coffee break 10:50 - 12:30 NEURAL NETWORKS & DISTRIBUTED ARTIFICIAL INTELLIGENCE 10:50 - 12:30 FUZZY LOGIC & NEURAL NETWORKS WORKSHOP 12:30 - 14:00 Lunch 14:00 - 15:30 Invited Lecture by LUIS B. ALMEIDA (IST - Portugal) "The Connectionist Paradigm and AI" 15:30 - 15:50 Coffee break 15:50 - 17:55 BELIEF REVISION & NON-MONOTONIC REASONING 15:50 - 17:55 FUZZY LOGIC & NEURAL NETWORKS WORKSHOP 15:50 - 17:55 APPLICATIONS OF EXPERT SYSTEMS WORKSHOP 20:00 - Welcome dinner Thursday - October, 5 95 ~~~~~~~~~~~~~~~~~~~~~~~~ 9:00 - 10:30 Invited Lecture by RODNEY BROOKS (MIT - USA) "The Evolutionist Approach - Past, Present and Future of AI" 10:30 - 10:50 Coffee break 10:50 - 12:30 FUZZY LOGIC & NEURAL NETWORKS WORKSHOP 10:50 - 12:30 APPLICATIONS OF EXPERT SYSTEMS WORKSHOP 10:50 - 11:40 ROBOTICS AND CONTROL 11:40 - 12:30 POSTER SECTION 12:30 - 14:00 Lunch 14:00 - 15:15 MACHINE LEARNING 14:00 - 15:15 APPLICATIONS OF AI TO ROBOTICS AND VISION SYSTEMS WORKSHOP 15:15 - 15:30 Coffee break 15:30 - 17:00 Invited Lecture by MARVIN MINSKY (MIT - USA) "Why Human Brains Can't Really Think" 17:15 - 18:30 Visit to the Madeira Wine Cellars Friday - October, 6 95 ~~~~~~~~~~~~~~~~~~~~~~ 9:00 - 10:30 INVITED LECTURE by Manuela Veloso (CMU - USA) "Planning and Learning in Intelligent Agents" 10:30 - 10:50 Coffee break 10:50 - 12:30 PLANNING AND CASE-BASED REASONING 10:50 - 12:30 CONSTRAINT-BASED REASONING 10:50 - 12:30 APPLICATIONS OF AI TO ROBOTICS AND VISION SYSTEMS WORKSHOP 12:30 - 14:00 Lunch 14:00 - 15:30 AUTOMATED REASONING AND THEOREM PROVING 14:00 - 15:30 GENETIC ALGORITHMS & THEORY OF COMPUTATION 14:00 - 15:30 APPLICATIONS OF AI TO ROBOTICS AND VISION SYSTEMS WORKSHOP 15:30 - 15:50 Coffee break 15:50 - 17:30 PANNEL (Foundations of AI) 18:00 - 19:00 APPIA meeting 20:00 Farewell dinner Saturday - October, 7 95 ~~~~~~~~~~~~~~~~~~~~~~~~ TOUR 1 - Island Tour (full day) TOUR 2 - Ribeiro Frio/Portela Walking Tour (full day) TOUR 3 - Eira do Serrado (half day) ====================================================================== PAPERS TO BE PRESENTED IN EACH SESSION ====================================================================== AUTOMATED REASONING AND THEOREM PROVING ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Terminological Meta-Reasoning by Reification and Multiple Contexts Klemens Schnattinger, Udo Hahn and Manfred Klenner CLIF, Freiburg University, Germany A New Continuous Propositional Logic Riccardo Poli, Mark Ryan and Aaron Sloman SCS, The University of Birmingham, UK Super-Polynomial Speed-Ups in Proof Length by New Tautologies Uwe Egly FG Intellektik, TH Darmstadt, Germany BELIEF REVISION ~~~~~~~~~~~~~~~ Belief Revision in Non-Monotonic Reasoning Jose Alferes, Luis Moniz Pereira and T. Przymusinski DM, U. Evora, and CRIA, U. Nova de Lisboa, Portugal A New Representation of JTMS Truong Quoc Dung IRIDIA, Universite Libre de Bruxelles, Belgium CONSTRAINT-BASED REASONING ~~~~~~~~~~~~~~~~~~~~~~~~~~ The Retrieval Problem in a Concept Language with Number Restrictions Aida Vitoria, Margarida Mamede and Luis Monteiro DI, Universidade Nova de Lisboa, Portugal Formalizing Local Propagation in Constraint Maintenance Systems Gilles Trombettoni INRIA-CERMICS, France A Dependency Parser of Korean Based on Connectionist/Symbolic Techniques Jong-Hyeok Lee and Geunbae Lee Pohang University of Science and Technology, Korea A Symbiotic Approach to Arc and Path Consistency Checking Pierre Berlandier INRIA-CERMICS, France DISTRIBUTED ARTIFICIAL INTELLIGENCE ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Where Do Intentions Come From?: A Framework for Goals and Intentions Adoption, Derivation and Evolution Graca Gaspar and Helder Coelho Faculdade de Ciencias de Lisboa, and INESC, Portugal A Closer Look to Artificial Learning Environments Helder Coelho, Augusto Eusebio and Ernesto Costa INESC, Portugal, and DEI, Universidade de Coimbra, Portugal Building Multi-Agent Societies from Descriptions to Systems: Inter-Layer Translations Helder Coelho, Luis Antunes and Luis Moniz INESC, Portugal GENETIC ALGORITHMS ~~~~~~~~~~~~~~~~~~ GA/TS: A Hybrid Approach for Job Shop Scheduling in a Production System Jose Ramon Zubizarreta and Javier Arrieta Facultad de Informatica de San Sebastian, Spain MACHINE LEARNING ~~~~~~~~~~~~~~~~ A Controlled Experiment: Evolution for Learning Difficult Image Classification Astro Teller and Manuela Veloso Carnegie Mellon University, USA Minimal Model Complexity Search Chris McConnell CMU School of Computer Science, USA Characterization of Classification Algorithms Joao Gama and Pavel Brazdil LIACC, Universidade do Porto, Portugal NEURAL NETWORKS ~~~~~~~~~~~~~~~ Neurons, Glia and the Borderline Between Subsymbolic and Symbolic Processing J. G. Wallace, K. Bluff Swinburne University of Technology, Australia NON-MONOTONIC REASONING ~~~~~~~~~~~~~~~~~~~~~~~ Arguments and Defeat in Argument-Based Nonmonotonic Reasoning Bart Verheij University of Limburg, The Netherlands A Preference Semantics for Ground Nonmonotonic Modal Logics Daniele Nardi and Riccardo Rosati DIS, Universita di Roma ``la Sapienza", Italy Logical Omniscience vs. Logical Ignorance On a Dilemma of Epistemic Logic Ho Ngoc Duc ILPS, University of Leipzig, Germany PLANNING AND CASE-BASED REASONING ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ On the Role of Splitting and Merging Past Cases for Generation of New Solutions Carlos Bento, Penousal Machado and Ernesto Costa DEI, Universidade de Coimbra, Portugal Theorem Proving by Analogy - A Compelling Example Erica Melis Department of AI, University of Edimburgh, Scotland Non-Atomic Actions in the Situation Calculus Jose Julio Alferes, Renwei Li and Luis Moniz Pereira CRIA and DCS, Universidade Nova de Lisboa, Portugal Planning under Uncertainty: A Qualitative Approach Nikos Karacapilidis FIT.KI, GMD, Sankt Augustin, Germany QUALITATIVE REASONING ~~~~~~~~~~~~~~~~~~~~~ Qualitative Reasoning under Uncertainty Daniel Pacholczyk DMI, U.F.R., Science d'Angers, France Systematic Construction of Qualitative Physics-Based Rules for Process Diagnostics Jaques Reifman and Thomas Y.C. Wei Argonne National Laboratory, USA ROBOTICS AND CONTROL ~~~~~~~~~~~~~~~~~~~~ Integrated Process Supervision (IPS): A Structured Approach to Expert Control Chai Quek, P.W. Ng, M. Pasquier Nanyang Technological University, Singapore Using Stochastic Grammars to Learn Robotic Tasks Pedro Lima and George Saridis ISR, Technical Univ. of Lisbon, Portugal, and Rensselaer Polytechnic Institute, USA THEORY OF COMPUTATION ~~~~~~~~~~~~~~~~~~~~~ Constraint Categorial Grammars Luis Damas and Nelma Moreira LIACC, Universidade do Porto, Portugal A New Translation Algorithm from Lambda Calculus into Combinatory Logic Sabine Broda and Luis Damas LIACC, Universidade do Porto, Portugal POSTER SECTION ~~~~~~~~~~~~~~ Interlocking Multi-Agent and Blackboard Architectures Bernhard Kipper DCS, University of Saarbrucken, Germany A Model Theory for Paraconsistent Logic Programming Carlos Viegas Damasio and Luis Moniz Pereira CRIA, and DCS, Universidade Nova de Lisboa, Portugal Promoting Software Reuse Through Explicit Knowledge Representation Carmen Fernandez-Chamizo, Pedro A. Gonzalez-Calero and Mercedes Gomez-Albarran Universidad Complutense, Spain Efficient Learning in Multi-Layered Perceptron Using the Grow-And-Learn Algorithm Gildas Cherruel, Bassel Solaiman and Yvon Autret Univ. de Bretagne Occidentale, and TNI, and ENSTB, France An Non-Diffident Combinatorial Optimization Algorithm Gilles Trombettoni and Bertrand Neveu INRIA-CERMICS, France Modelling Diagnosis Systems with Logic Programming Iara Mora, Jose Alferes CRIA, U. Nova de Lisboa, and DM, U. Evora, Portugal Agreement: A Logical Approach to Approximate Reasoning Luis Custodio and Carlos Pinto-Ferreira ISR, Technical University of Lisbon, Portugal Constructing Extensions by Resolving a System of Linear Equations Messaoudi Nadia Universite Aix-Marseille II, France Presenting Significant Information in Expert System Explanation Michael Wolverton Daresbury Rutherford Appleton Laboratory, UK A Cognitive Model of Problem Solving with Incomplete Information Nathalie Chaignaud LIPN, Universite Paris-Nord, France Filtering Software Specifications Written In Natural Language Nuria Castell and Angels Hernandez Universitat Politecnica de Catalunya, Spain Parsimonious Diagnosis in SNePS Pedro A. Matos and Joao P. Martins DEM, Technical University of Lisbon, Portugal Syntactic and Semantic Filtering in a Chart Parser Sayan Bhattacharyya, Steven L. Lytinen University of Michigan, and DePaul University, USA GA Approach to solving Multiple Vehicle Routing Problem Slavko Krajcar, Davor Skrlec, Branko Pribicevic and Snjezana Blagajac Faculty of Electrical Eng. and Computing, Croatia Multilevel Refinement Planning in an Interval-Based Temporal Logic Werner Stephan and Susanne Biundo German Research Center for AI, Germany ====================================================================== ENQUIRIES ADDRESS ====================================================================== EPIA'95 - INESC E-mail: epia95@inesc.pt Av. Alves Redol, 9 Fax: 351-1-525843 1000 Lisboa Voice: 351-1-3100325 PORTUGAL Home Page: http://www.isr.ist.utl.pt/~cpf/epia95 ====================================================================== SUPPORTERS ====================================================================== Banco Nacional Ultramarino Governo Regional da Madeira Instituto Superior Tecnico SISCOG - Sistemas Cognitivos INESC CITMA IBM TAPair Portugal ------------------------------ End of ML-LIST (Digest format) **************************************** From mdorigo@ulb.ac.be Sat Jul 29 04:32:39 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 29 Jul 95 04:32:35 -0500; AA08137 Received: from bilby.cs.uwa.oz.au by lucy.cs.wisc.edu; Sat, 29 Jul 95 04:32:28 -0500 Received: from (mafm@parma.cs.uwa.oz.au [130.95.1.7]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id PAA05382; Sat, 29 Jul 1995 15:51:58 +0800 Message-Id: <199507290751.PAA05382@cs.uwa.oz.au> From: mdorigo@ulb.ac.be (Marco DORIGO) To: reinforce@cs.uwa.edu.au Subject: WWW Page: SECOND EUROPEAN WORKSHOP ON REINFORCEMENT LEARNING Date: Fri, 28 Jul 1995 15:15:32 +0200 I prepared a WWW page regarding the SECOND EUROPEAN WORKSHOP ON REINFORCEMENT LEARNING. The page URL is: http://iridia.ulb.ac.be/EWRL2/EWRL2.html Marco Dorigo From chandler@kryton.ntu.ac.uk Sat Jul 29 05:16:17 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 29 Jul 95 05:16:12 -0500; AA08418 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sat, 29 Jul 95 05:16:09 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa16290; 28 Jul 95 13:26:08 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa16282; 28 Jul 95 13:02:41 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00604; 28 Jul 95 13:01:57 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa27212; 28 Jul 95 7:24:43 EDT Received: from dns0.ntu.ac.uk by EDRC.CMU.EDU id aa08626; 28 Jul 95 7:24:17 EDT Received: by dns0.ntu.ac.uk (5.65/DEC-Ultrix/4.3) id AA00202; Fri, 28 Jul 1995 12:14:53 +0100 From: chandler@kryton.ntu.ac.uk Received: by kryton.ntu.ac.uk (5.0/SMI-SVR4) id AA16372; Fri, 28 Jul 1995 12:24:11 +0000 Date: Fri, 28 Jul 1995 12:24:11 +0000 Message-Id: <9507281124.AA16372@kryton.ntu.ac.uk> To: Connectionists@cs.cmu.edu Subject: NEURO-FUZZY CONTROL POSITION Cc: chandler@kryton.ntu.ac.uk X-Sun-Charset: US-ASCII Content-Length: 1848 ******************* NEURO-FUZZY CONTROL POSITION *********************** at ******************* The Nottingham Trent University *********************** RESEARCH FELLOW/ASSISTANT ------------------------------------------------------------------------------- The Manufacturing Automation Research Group within the Department of Manufacturing Engineering, working in collaboration with the Real Time Machine Control Group of the Department of Computing, is seeking a full-time researcher for an initial two year appointment to join an active resarch group working in fuzzy control techniques applied to the adaptive control of the complex process of stencil printing of solder paste. For this post we require a numerate graduate with knowledge of computer control techniques and preferably an awareness of neuro-fuzzy methodologies. Previous experience of the electronics industry is also desirable. Individuals who have completed a PhD and graduates with a proven ability in complex system analysis and control are particularly welcome to apply. Salary will be in the Research Fellow Scale ( 12,756 - 21,262 p.a.) or the Research Assistant Scale ( 9,921 - 12,048 p.a.). Closing date 31st August 1995. Post No. G0493. For more information about this post contact : Martin Howarth Manufacturing Automation Research Group Department of Manufacturing Engineering The Nottingham Trent University Burton Street Nottingham NG1 4BU ENGLAND TEL: +44 (115) 941 8418 (ext. 4110) E-MAIL : man3howarm@ntu.ac.uk or Dr. Pete Thomas Real Time Machine Control Group Department of Computing The Nottingham Trent University Burton Street Nottingham NG1 4BU ENGLAND TEL: +44 (115) 941 8418 (ext. 2901) Alternatively use the HTML Form at the URL : http://marg.ntu.ac.uk/marg/vacancy895.html From john@dcs.rhbnc.ac.uk Sat Jul 29 05:16:18 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 29 Jul 95 05:16:15 -0500; AA08424 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sat, 29 Jul 95 05:16:12 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa16477; 28 Jul 95 16:09:18 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa16475; 28 Jul 95 15:55:53 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00683; 28 Jul 95 15:55:02 EDT From: John Shawe-Taylor Message-Id: <199507281443.PAA21814@platon.cs.rhbnc.ac.uk> To: Connectionists@cs.cmu.edu Subject: Technical Report Series in Neural and Computational Learning Date: Fri, 28 Jul 95 15:43:55 +0100 The European Community ESPRIT Working Group in Neural and Computational Learning Theory (NeuroCOLT): one new report available ---------------------------------------- NeuroCOLT Technical Report NC-TR-95-050: ---------------------------------------- Learning Ordered Binary Decision Diagrams by Ricard Gavald\`a and David Guijarro, Universitat Polit\`ecnica de Catalunya Abstract: This note studies the learnability of ordered binary decision diagrams (obdds). We give a polynomial-time algorithm using membership and equivalence queries that finds the minimum obdd for the target respecting a given ordering. We also prove that both types of queries and the restriction to a given ordering are necessary if we want minimality in the output, unless P=NP. If learning has to occur with respect to the optimal variable ordering, polynomial-time learnability implies the approximability of two NP-hard optimization problems: the problem of finding the optimal variable ordering for a given obdd and the Optimal Linear Arrangement problem on graphs. ----------------------- The Report NC-TR-95-050 can be accessed and printed as follows % ftp cscx.cs.rhbnc.ac.uk (134.219.200.45) Name: anonymous password: your full email address ftp> cd pub/neurocolt/tech_reports ftp> binary ftp> get nc-tr-95-050.ps.Z ftp> bye % zcat nc-tr-95-050.ps.Z | lpr -l Similarly for the other technical report. Uncompressed versions of the postscript files have also been left for anyone not having an uncompress facility. A full list of the currently available Technical Reports in the Series is held in a file `abstracts' in the same directory. The files may also be accessed via WWW starting from the NeuroCOLT homepage: http://www.dcs.rhbnc.ac.uk/neural/neurocolt.html Best wishes John Shawe-Taylor From honavar@iastate.edu Sat Jul 29 19:36:26 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 29 Jul 95 19:36:24 -0500; AA16366 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sat, 29 Jul 95 19:36:22 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa18302; 29 Jul 95 17:21:01 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa18300; 29 Jul 95 17:06:48 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01674; 29 Jul 95 17:06:20 EDT Received: from pv031e.vincent.iastate.edu by B.GP.CS.CMU.EDU id aa08239; 28 Jul 95 18:37:50 EDT Received: by pv031e.vincent.iastate.edu with sendmail-5.65 id ; Fri, 28 Jul 1995 17:37:40 -0500 Message-Id: <9507282237.AA09329@pv031e.vincent.iastate.edu> To: connectionists@B.GP.CS.CMU.EDU Date: Fri, 28 Jul 1995 17:37:39 CDT From: Vasant Honavar The following recent publications of the Artificial Intelligence Research Group (URL http://www.cs.iastate.edu/~honavar/aigroup.html) can be accessed on WWW via the URL http://www.cs.iastate.edu/~honavar/publist.html 1. Chen, C-H. and Honavar, V. (1995). A Neural Memory Architecture for Content as well as Address-Based Storage and Recall: Theory and Applications Paper under review. Draft available as ISU CS-TR 95-03. 2. Chen, C-H. and Honavar, V. (1995). A Neural Network Architecture for High-Speed Database Query Processing. Paper under review. Draft available as ISU CS-TR 95-11. 3. Chen, C-H. and Honavar, V. (1995). A Neural Architecture for Syntax Analysis. Paper under review. Draft available as ISU-CS-TR 95-18. 4. Mikler, A., Wong, J., and Honavar, V. (1995). Quo-Vadis - Adaptive Heuristics for Routing in Large Communication Networks. Under review. Draft available as ISU CS-TR 95-10. 5. Mikler, A., Wong, J., and Honavar, V. (1995). An Object-Oriented Approach to Modelling and Simulation of Routing in Large Communication Networks. Under review. Draft available as: ISU CS-TR 95-09. 6. Balakrishnan, K. and Honavar, V. (1995). Evolutionary Design of Neural Architectures - A Preliminary Taxonomy and Guide to Literature. Available as: ISU CS-TR 95-01. 7. Parekh, R. & Honavar, V. (1995). An Interactive Algorithm for Regular Language Learning. Available as: ISU CS-TR 95-02. 8. Balakrishnan, K. and Honavar, V. (1995) Properties of Genetic Representations of Neural Architectures. In: Proceedings of the World Congress on Neural Networks. Washington, D.C., 1995. Available as: ISU CS-TR 95-13. 9. Chen, C-H., Parekh, R., Yang, J., Balakrishnan, K. and Honavar, V. (1995). Analysis of Decision Boundaries Generated by Constructive Neural Network Learning Algorithms. In: Proceedings of the World Congress on Neural Networks. Washington, D.C., 1995. Available as: ISU CS-TR 95-12. The following publications will be available on line shortly (within the next few weeks): 1. Kirillov, V. and Honavar, V. (1995). Simple Stochastic Temporal Constraint Networks. Draft available as: ISU CS-TR 95-16. 2. Mikler, A., Wong, J., and Honavar, V. (1995). Utility-Theoretic Heuristics for Routing in Large Telecommunication Networks. Draft available as: ISU CS-TR 95-14. 3. Parekh, R., Yang, J., and Honavar, V. (1995). Constructive Neural Network Learning Algorithms for Multi-Category Pattern Classification. Draft available as: ISU CS-TR 95-15. 4. Yang, J., Parekh, R., and Honavar, V. (1995). Comparison of Variants of Single-Layer Perceptron Algorithms on Non-Separable Data. Draft available as: ISU CS-TR 95-19. The WWW page also contains pointers to other older publications some of which are available on line. Those who don't have access to a WWW browser can obtain ISU CS tech reports by sending email to almanac@cs.iastate.edu with BODY (not SUBJECT) "send tr catalog" and following the instructions that you will receive in the reply from almanac. Sorry, no hard copies are available. Best regards, Vasant Honavar Artificial Intelligence Research Group 226 Atanasoff Hall Department of Computer Science Iowa State University Ames, IA 50011-1040 email: honavar@cs.iastate.edu www: http://www.cs.iastate.edu/~honavar/homepage.html From stiber@bpe.es.osaka-u.ac.jp Sat Jul 29 22:18:08 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 29 Jul 95 22:18:05 -0500; AA19998 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sat, 29 Jul 95 22:18:03 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab18302; 29 Jul 95 17:22:19 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab18300; 29 Jul 95 17:06:53 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01679; 29 Jul 95 17:06:37 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa11385; 28 Jul 95 23:44:42 EDT Received: from aoi.bpe.es.osaka-u.ac.jp by RI.CMU.EDU id aa25767; 28 Jul 95 23:44:10 EDT Received: (from stiber@localhost) by aoi.bpe.es.osaka-u.ac.jp (8.6.9+2.4Wb3/3.3Wb95021312) id MAA05348; Sat, 29 Jul 1995 12:43:55 +0900 Date: Sat, 29 Jul 1995 12:43:55 +0900 From: Stiber Message-Id: <199507290343.MAA05348@aoi.bpe.es.osaka-u.ac.jp> To: Connectionists@cs.cmu.edu Subject: two new papers on transient responses of pacemakers at Neuroprose Ftp-Host: archive.cis.ohio-state.edu Ftp-File: pub/neuroprose/stiber.transcomp.ps.Z Ftp-File: pub/neuroprose/stiber.transhyst.ps.Z The following 2 papers are now available for copying from the Neuroprose repository: stiber.transcomp.ps.Z, stiber.transhyst.ps.Z. stiber.transcomp.ps.Z (194085 bytes, 10 pages) M. Stiber, R. Ieong, J.P. Segundo Responses to Transients in Living and Simulated Neurons (submitted to NIPS'95; also technical report HKUST-CS95-26) This paper is concerned with synaptic coding when inputs to a neuron change over time. Experiments were performed on a living and simulated embodiment of a prototypical inhibitory synapse. Results indicate that the neuron's reponse lags its input by a fixed delay. Based on this, we present a qualitative model for phenomena previously observed in the living preparation, including hysteresis and dependence of discharge regularity on rate of change of presynaptic spike rate. As change is the rule rather than the exception in life, understanding neurons' responses to nonstationarity is essential for understanding their function. stiber.transhyst.ps.Z (244297 bytes, 13 pages) M. Stiber and R. Ieong Hysteresis and Asymmetric Sensitivity to Change in Pacemaker Responses to Inhibitory Input Transients (in press, Proc. Int. Conf. on Brain Processes, Theories, and Models. W.S. McCulloch: 25 Years in Memoriam; also technical report HKUST-CS95-29) The coding of presynaptic spike trains to postsynaptic ones is the unit of computation in nervous systems. While such coding has been examined in detail under stationary input conditions, the effects of changing inputs have until recently been understood only superficially. When a neuron receives transient inputs with monotonically changing instantaneous rate, its response along time depends not only on the rate at that time, but also on the sign and magnitude of its rate of change. This has been shown previously for the living embodiment of a prototypical inhibitory synapse. We present simulations of a physiological model of this living preparation which reproduce its behaviors. Based on these results, we propose a simple model for the neuron's response involving a constant delay between its input and internal state. This is then generalized to a nonlinear dynamical model of any similar system with an internal state which lags its input. ** If you absolutely, positively can't produce your own hardcopy (or induce a friend to do so for you), hardcopies can be requested in writing to: Technical Reports, Department of Computer Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; don't forget to include the TR number. ** --- Dr. Michael Stiber stiber@bpe.es.osaka-u.ac.jp c/o Prof. S. Sato Department of Biophysical Engineering Osaka University Toyonaka 560 Osaka, Japan On leave from: Department of Computer Science stiber@cs.ust.hk The Hong Kong University of Science & Technology tel: +852-2358-6981 Clear Water Bay, Kowloon, Hong Kong fax: +852-2358-1477