From mhb0@Lehigh.EDU Sun Jun 11 22:17:14 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sun, 11 Jun 95 22:17:11 -0500; AA16713 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sun, 11 Jun 95 22:17:07 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa17794; 11 Jun 95 21:53:41 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa17792; 11 Jun 95 21:33:17 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01218; 11 Jun 95 21:32:48 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa20762; 11 Jun 95 16:02:01 EDT Received: from nss1.CC.Lehigh.EDU by CS.CMU.EDU id aa13090; 11 Jun 95 16:01:32 EDT Received: from ns4-1.CC.Lehigh.EDU (root@ns4-1.CC.Lehigh.EDU [128.180.1.42]) by nss1.CC.Lehigh.EDU (8.6.10/8.6.9) with ESMTP id QAA35335 for ; Sun, 11 Jun 1995 16:01:29 -0400 Received: (mhb0@localhost) by ns4-1.CC.Lehigh.EDU (8.6.10/8.6.9) id PAA51802; Sun, 11 Jun 1995 15:57:29 -0400 Message-Id: <199506111957.PAA51802@ns4-1.CC.Lehigh.EDU> Date: Sun, 11 Jun 1995 15:57:26 EDT From: "Mark H. Bickhard" X-Mailer: SENDM [Version 2.0.15] Subject: New Book Announcement To: connectionists@cs.cmu.edu BOOK ANNOUNCEMENT Foundational Issues in Artificial Intelligence and Cognitive Science: Impasse and Solution. Elsevier Science 1995 Mark H. Bickhard Lehigh University mhb0@lehigh.edu Loren Terveen AT&T Bell Laboratories terveen@research.att.com SHORT DESCRIPTION The book focuses on a conceptual flaw in contemporary artificial intelligence and cognitive science. Many people have discovered diverse manifestations and facets of this flaw, but the central conceptual impasse is at best only partially perceived. Its consequences, nevertheless, visit themselves as distortions and failures of multiple research projects - and make impossible the ultimate aspirations of the fields. The impasse concerns a presupposition concerning the nature of representation - that all representation has the nature of encodings: encodingism. Encodings certainly exist, but encoding*ism* is at root logically incoherent; any *programmatic* research predicated on it is doomed to distortion and ultimate failure. The impasse and its consequences - and steps away from that impasse - are explored in a large number of projects and approaches. These include SOAR, CYC, PDP, situated cognition, subsumption architecture robotics, and the frame problems - a general survey of the current research in AI and Cognitive Science emerges. Interactivism, an alternative model of representation, is proposed and examined. SYNOPSIS The central point of Foundational Issues in Artificial Intelligence and Cognitive Science - Impasse and Solution is that there is a conceptual flaw in contemporary approaches to artificial intelligence and cognitive science, a flaw that makes impossible the ultimate aspirations of these fields. Many people have discovered diverse manifestations and facets of this flaw, but the central conceptual impasse is only partially perceived. The consequences, nevertheless, visit themselves as distortions and failures of research projects across the fields. The locus of the impasse concerns a common assumption or presupposition that underlies all parts of the field - a presupposition concerning the nature of representation. We call this assumption "encodingism", the assumption that representation is fundamentally constituted as encodings. This assumption, in fact, has been dominant throughout Western history. We argue that it is at root logically incoherent, and, therefore, that any programmatic research predicated on it is doomed to distortion and ultimate failure. On the other hand, encodings clearly do exist, and therefore are clearly possible, and we show how that could be - but they cannot be the foundational form of representation. Similarly, contemporary encoding approaches are enormously powerful, and major advances have been made within these dominant programmatic frameworks - but the encodingism flaw in those frameworks limit their ultimate possibilities, and will frustrate efforts toward the programmatic goal of understanding and constructing minds. The book characterizes and demonstrates this impasse, discusses a number of partial recognitions of and movements away from it, and then traces its consequences in a large number of projects and approaches within the fields. These include SOAR, CYC, PDP, situated cognition, subsumption architecture robotics, and the frame problems. In surveying the consequences of the impasse, we also provide a general survey of the current research in AI and Cognitive Science per se. We do not propose an unsolvable impasse, and, in fact, present an alternative that does resolve that impasse. This is developed for contrast, for perspective, to demonstrate that there is an alternative, and to explore some of its nature. We end with an exploration of some of the architectural implications of the alternative - called interactivism - and argue that such architectures are 1) not subject to the encodingism incoherence 2) more powerful than Turing machines, 3) more consistent with properties of central nervous system functioning than other contemporary approaches, and 4) capable of resolving the many problematics in the field that we argue are in fact manifestations of the underlying impasse. The audience for this book will include researchers, academics, and students in artificial intelligence, cognitive science, robotics, cognitive psychology, philosophy of mind and language, natural language processing, connectionism, and learning. The focus of the book is on the nature of representation, and representation permeates everywhere - so also, therefore, do the implications of our critique and our alternative permeate everywhere. CONTENTS Preface xi Introduction 1 A PREVIEW 2 I GENERAL CRITIQUE 5 1 Programmatic Arguments 7 CRITIQUES AND QUALIFICATIONS 8 DIAGNOSES AND SOLUTIONS 8 IN-PRINCIPLE ARGUMENTS 9 2 The Problem of Representation 11 ENCODINGISM 11 Circularity 12 Incoherence - The Fundamental Flaw 13 A First Rejoinder 15 The Necessity of an Interpreter 17 3 Consequences of Encodingism 19 LOGICAL CONSEQUENCES 19 Skepticism 19 Idealism 20 Circular Microgenesis 20 Incoherence Again 20 Emergence 21 4 Responses to the Problems of Encodings 25 FALSE SOLUTIONS 25 Innatism 25 Methodological Solipsism 26 Direct Reference 27 External Observer Semantics 27 Internal Observer Semantics 28 Observer Idealism 29 Simulation Observer Idealism 30 SEDUCTIONS 31 Transduction 31 Correspondence as Encoding: Confusing Factual and Epistemic Correspondence 32 5 Current Criticisms of AI and Cognitive Science 35 AN APORIA 35 Empty Symbols 35 ENCOUNTERS WITH THE ISSUES 36 Searle 36 Gibson 40 Piaget 40 Maturana and Varela 42 Dreyfus 42 Hermeneutics 44 6 General Consequences of the Encodingism Impasse 47 REPRESENTATION 47 LEARNING 47 THE MENTAL 51 WHY ENCODINGISM? 51 II INTERACTIVISM: AN ALTERNATIVE TO ENCODINGISM 53 7 The Interactive Model 55 BASIC EPISTEMOLOGY 56 Representation as Function 56 Epistemic Contact: Interactive Differentiation and Implicit Definition 60 Representational Content 61 EVOLUTIONARY FOUNDATIONS 65 SOME COGNITIVE PHENOMENA 66 Perception 66 Learning 69 Language 71 8 Implications for Foundational Mathematics 75 TARSKI 75 Encodings for Variables and Quantifiers 75 Tarski's Theorems and the Encodingism Incoherence 76 Representational Systems Adequate to Their Own Semantics 77 Observer Semantics 78 Truth as a Counterexample to Encodingism 79 TURING 80 Semantics for the Turing Machine Tape 81 Sequence, But Not Timing 81 Is Timing Relevant to Cognition? 83 Transcending Turing Machines 84 III ENCODINGISM: ASSUMPTIONS AND CONSEQUENCES 87 9 Representation: Issues within Encodingism 89 EXPLICIT ENCODINGISM IN THEORY AND PRACTICE 90 Physical Symbol Systems 90 The Problem Space Hypothesis 98 SOAR 100 PROLIFERATION OF BASIC ENCODINGS 106 CYC - Lenat's Encyclopedia Project 107 TRUTH-VALUED VERSUS NON-TRUTH-VALUED 118 Procedural vs Declarative Representation 119 PROCEDURAL SEMANTICS 120 Still Just Input Correspondences 121 SITUATED AUTOMATA THEORY 123 NON-COGNITIVE FUNCTIONAL ANALYSIS 126 The Observer Perspective Again 128 BRIAN SMITH 130 Correspondence 131 Participation 131 No Interaction 132 Correspondence is the Wrong Category 133 ADRIAN CUSSINS 134 INTERNAL TROUBLES 136 Too Many Correspondences 137 Disjunctions 138 Wide and Narrow 140 Red Herrings 142 10 Representation: Issues about Encodingism 145 SOME EXPLORATIONS OF THE LITERATURE 145 Stevan Harnad 145 Radu Bogdan 164 Bill Clancey 169 A General Note on Situated Cognition 174 Rodney Brooks: Anti-Representationalist Robotics 175 Agre and Chapman 178 Benny Shanon 185 Pragmatism 191 Kuipers' Critters 195 Dynamic Systems Approaches 199 A DIAGNOSIS OF THE FRAME PROBLEMS 214 Some Interactivism-Encodingism Differences 215 Implicit versus Explicit Classes of Input Strings 217 Practical Implicitness: History and Context 220 Practical Implicitness: Differentiation and Apperception 221 Practical Implicitness: Apperceptive Context Sensitivities 222 A Counterargument: The Power of Logic 223 Incoherence: Still another corollary 229 Counterfactual Frame Problems 230 The Intra-object Frame Problem 232 11 Language 235 INTERACTIVIST VIEW OF COMMUNICATION 237 THEMES EMERGING FROM AI RESEARCH IN LANGUAGE 239 Awareness of the Context-dependency of Language 240 Awareness of the Relational Distributivity of Meaning 240 Awareness of Process in Meaning 242 Toward a Goal-directed, Social Conception of Language 247 Awareness of Goal-directedness of Language 248 Awareness of Social, Interactive Nature of Language 252 Conclusions 259 12 Learning 261 RESTRICTION TO A COMBINATORIC SPACE OF ENCODING 261 LEARNING FORCES INTERACTIVISM 262 Passive Systems 262 Skepticism, Disjunction, and the Necessity of Error for Learning 266 Interactive Internal Error Conditions 267 What Could be in Error? 270 Error as Failure of Interactive Functional Indications - of Interactive Implicit Predications 270 Learning Forces Interactivism 271 Learning and Interactivism 272 COMPUTATIONAL LEARNING THEORY 273 INDUCTION 274 GENETIC AI 275 Overview 276 Convergences 278 Differences 278 Constructivism 281 13 Connectionism 283 OVERVIEW 283 STRENGTHS 286 WEAKNESSES 289 ENCODINGISM 292 CRITIQUING CONNECTIONISM AND AI LANGUAGE APPROACHES 296 IV SOME NOVEL ARCHITECTURES 299 14 Interactivism and Connectionism 301 INTERACTIVISM AS AN INTEGRATING PERSPECTIVE 301 Hybrid Insufficiency 303 SOME INTERACTIVIST EXTENSIONS OF ARCHITECTURE 304 Distributivity 304 Metanets 307 15 Foundations of an Interactivist Architecture 309 THE CENTRAL NERVOUS SYSTEM 310 Oscillations and Modulations 310 Chemical Processing and Communication 311 Modulatory "Computations" 312 The Irrelevance of Standard Architectures 313 A Summary of the Argument 314 PROPERTIES AND POTENTIALITIES 317 Oscillatory Dynamic Spaces 317 Binding 318 Dynamic Trajectories 320 "Formal" Processes Recovered 322 Differentiators In An Oscillatory Dynamics 322 An Alternative Mathematics 323 The Interactive Alternative 323 V CONCLUSIONS 325 16 Transcending the Impasse 327 FAILURES OF ENCODINGISM 327 INTERACTIVISM 329 SOLUTIONS AND RESOURCES 330 TRANSCENDING THE IMPASSE 331 References 333 Index 367 PREFACE Artificial Intelligence and Cognitive Science are at a foundational impasse which is at best only partially recognized. This impasse has to do with assumptions concerning the nature of representation: standard approaches to representation are at root circular and incoherent. In particular, Artificial Intelligence research and Cognitive Science are conceptualized within a framework that assumes that cognitive processes can be modeled in terms of manipulations of encoded symbols. Furthermore, the more recent developments of connectionism and Parallel Distributed Processing, even though the issue of manipulation is contentious, share the basic assumption concerning the encoding nature of representation. In all varieties of these approaches, representation is construed as some form of encoding correspondence. The presupposition that representation is constituted as encodings, while innocuous for *some applied* Artificial Intelligence research, is fatal for the further reaching programmatic aspirations of both Artificial Intelligence and Cognitive Science. First, this encodingist assumption constitutes a *presupposition* about a basic aspect of mental phenomena - representation - rather than constituting a *model* of that phenomenon. Aspirations of Artificial Intelligence and Cognitive Science to provide any foundational account of representation are thus doomed to circularity: the encodingist approach presupposes what it purports to be (programmatically) able to explain. Second, the encoding assumption is not only itself in need of explication and modeling, but, even more critically, the standard presupposition that representation is *essentially* constituted as encodings is logically fatally flawed. This flaw yields numerous subsidiary consequences, both conceptual and applied. This book began as an article attempting to lay out this basic critique at the programmatic level. Terveen suggested that it would be more powerful to supplement the general critique with explorations of actual projects and positions in the fields, showing how the foundational flaws visit themselves upon the efforts of researchers. We began that task, and, among other things, discovered that there is no natural closure to it - there are always more positions that could be considered, and they increase in number exponentially with time. There is no intent and no need, however, for our survey to be exhaustive. It is primarily illustrative and demonstrative of the problems that emerge from the underlying programmatic flaw. Our selections of what to include in the survey have had roughly three criteria. We favored: 1) major and well known work, 2) positions that illustrate interesting deleterious consequences of the encodingism framework, and 3) positions that illustrate the existence and power of moves in the direction of the alternative framework that we propose. We have ended up, *en passant*, with a representative survey of much of the field. Nevertheless, there remain many more positions and research projects that we would like to have been able to address. MAIN FEATURES Identifies a fundamental premise about the nature of representation that underlies much of Cognitive Science - that representation is constituted as encodings. Explores fatal flaws with this premise. Surveys major projects within Cognitive Science and Artificial Intelligence. Shows how they embody the encodingism premise, and how they are limited by it. Identifies movements within Cognitive Science and AI away from encodingism. Presents an alternative to encodingism - interactivism. Demonstrates that interactivism avoids the fatal flaws of encodingisms, and that it provides a coherent framework for understanding representation. Unifies insights from the various movements in Cognitive Science away from encodingism. Sketches an interactivist cognitive architecture. FIELDS OF INTEREST Cognitive Science Simulation of Cognitive Processes Artificial Intelligence, Knowledge Engineering, Expert Systems Human Information Processing Philosophy of Language Philosophy of Mind Cognitive Psychology Robotics Artificial Life Autonomous Agents Dynamic Systems and Behavior Learning Theory of Computation Semantics Pragmatics Connectionism Linguistics Neuroscience Bickhard, M. H., Terveen, L. (1995). Foundational Issues in Artificial Intelligence and Cognitive Science - Impasse and Solution. Elsevier Scientific. ISBN 0 444 82048 5 In the US/Canada orders may be placed with: Elsevier Science P.O. Box 945 New York, NY 10159-0945 Phone (212) 633-3750 Fax (212) 633-3764 Email: usorders-f@elsevier.com Elsevier has given this book an unfortunately high price: Dfl. 240 -- US$ 141.25. We deeply regret that. Nevertheless, we suggest that it is well worth taking a look at, whether by purchase, local library, or inter-library loan. From georg@ai.univie.ac.at Tue Jun 13 13:51:58 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 13 Jun 95 13:51:56 -0500; AA11855 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 13 Jun 95 13:51:53 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa19854; 13 Jun 95 12:49:50 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa19852; 13 Jun 95 12:27:48 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02726; 13 Jun 95 12:27:00 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa11342; 13 Jun 95 9:28:07 EDT Received: from jedlesee.ai.univie.ac.at by RI.CMU.EDU id aa29590; 13 Jun 95 9:26:23 EDT Received: (from georg@localhost) by jedlesee.ai.univie.ac.at (8.6.10/8.6.9) id PAA29403 for connectionists@cs.cmu.edu; Tue, 13 Jun 1995 15:26:13 +0200 From: Georg Dorffner Message-Id: <199506131326.PAA29403@jedlesee.ai.univie.ac.at> Subject: Neural Nets and EEG: WWW page and workshop To: connectionists@cs.cmu.edu Date: Tue, 13 Jun 1995 15:26:13 +0200 (MET DST) X-Mailer: ELM [version 2.4 PL24] Mime-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit Content-Length: 3172 The European BIOMED-1 project ========================================================================= A N N D E E (Enhancement of EEG-Based Diagnosis of Neurological and Psychiatric Disorders Using Artificial Neural Networks) ========================================================================= announces its WWW home page: http://www.ai.univie.ac.at/oefai/nn/anndee/ ANNDEE is a concerted action sponsored by the European Commission and the Austrian Federal Ministry of Science, Research, and the Arts. It is devoted to coordinating research at several European centers aimed at processing EEG data using neural networks, in order to enhance diagnosis based on EEG. Among the application areas focused upon within ANNDEE are: - detection and classification of psychoses (e.g. schizophrenia) - detection and classification of degenerative diseases (e.g. Parkinson's) - automatic sleep staging and detection of sleep disorders (e.g. apneua, arousals) - spike detection in epilepsy - classification of single-trial, event-related EEG (e.g. for aiding handicapped) The home page at the above URL does not only give information about the ANNDEE project but is aimed at growing into a comprehensive server for anyone interested in this topic. Currently it includes - a list of partners and associated sites - a list of other sites on the Web - a search form for bibliographical references - links to publicly available EEG data - a list of important events =========================I M P O R T A N T !============================== Currently, some of the pages are still rather short. In order to make these services as complete as possible, we urge everyone working on EEG data processing with neural networks, to send us their - address (incl. URL, if applicable) - description of their work - references - links to available data (this is not restricted to European sites!!) Send email to: anndee-admin@ai.univie.ac.at Questions concerning the scientific part of the project should be directed to: georg@ai.univie.ac.at (Georg Dorffner) ========================================================================== Check it out!! This service is part of the WWW server at the Austrian Research Institute for Artificial Intelligence Vienna, Austria __________________________________________________________________________ First Announcement: Public ANNDEE Meeting The ANNDEE project announces its first public workshop ======================================= Neural Network-Based EEG Analysis ======================================= June 29-30, 1995 Graz, Austria This workshop comprises lectures by ANNDEE participants as well as invited speakers, such as J. Kangas (Finland). It also includes tutorials on LVQ and SOM (self-organizing feature maps). For more information see http://www-dpmi.tu-graz.ac.at/Workshop/Workshop.html or send email to: pregenz@dpmi.tu-graz.ac.at (Martin Pregenzer) ______________________________________________________________ From dawei@venezia.rockefeller.edu Tue Jun 13 21:51:28 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 13 Jun 95 21:51:25 -0500; AA16325 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 13 Jun 95 21:51:22 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa20273; 13 Jun 95 18:34:49 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa20271; 13 Jun 95 18:25:55 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02867; 13 Jun 95 18:25:11 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa13930; 13 Jun 95 12:43:26 EDT Received: from venezia.rockefeller.edu by EDRC.CMU.EDU id aa28133; 13 Jun 95 12:42:11 EDT Received: by venezia.rockefeller.edu (920330.SGI/920502.SGI) for Connectionists@cs.cmu.edu id AA26190; Tue, 13 Jun 95 12:42:17 -0400 Date: Tue, 13 Jun 95 12:42:17 -0400 From: Dawei Dong Message-Id: <9506131642.AA26190@venezia.rockefeller.edu> To: Connectionists@cs.cmu.edu Subject: two papers on temporal information processing by Dong & Atick A theory of temporal information processing in neural systems: how the early visual pathways, such as LGN, temporally modulate the incoming signals of natural scenes? The following two papers explore the above subject by 1) measuring the temporal power spectrum of natural time-varying images to reveal the underlying statistical regularities, and, 2) based on the measurements, using information theory to predict the optimal temporal filter which is shown in quantitative agreements with physiological experiments. Dawei Dong 1) ftp://venezia.rockefeller.edu/dawei/papers/95-TIME.ps.Z (213K, 19 pages) Statistics of natural time-varying images Dawei W. Dong and Joseph J. Atick Computational Neuroscience Laboratory The Rockefeller University 1230 York Avenue New York, NY 10021-6399 Abstract Natural time-varying images possess substantial spatiotemporal correlations. We measure these correlations --- or equivalently the power spectrum --- for an ensemble of more than a thousand segments of motion pictures, and we find significant regularities. More precisely, our measurements show that the dependence of the power spectrum on the spatial frequency, $f$, and temporal frequency, $w$, is in general nonseparable and is given by $f^{-m-1} F(w/f)$, where $F(w/f)$ is a nontrivial function of the ratio $w/f$. We give a theoretical derivation of this scaling behaviour and show that it emerges from objects with a static power spectrum $\sim f^{-m}$, appearing at a wide range of depths and moving with a distribution of velocities relative to the observer. We show that in the regime of relatively high temporal and low spatial frequencies, the power spectrum becomes independent of the details of the velocity distribution and it is separable into the product of spatial and temporal power spectra with the temporal part given by the universal power-law $\sim w^{-2}$. Making some reasonable assumptions about the form of the velocity distribution we derive an analytical expression for the spatiotemporal power spectrum which is in excellent agreement with the data for the entire range of spatial and temporal frequencies of our measurements. The results in this paper have direct implications to neural processing of time-varying images in the visual pathway. (Accepted for publication in Network: Computation in Neural Systems) 2) ftp://venezia.rockefeller.edu/dawei/papers/95-LGN.ps.Z (279K, 26 pages) Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus Dawei W. Dong and Joseph J. Atick Computational Neuroscience Laboratory The Rockefeller University 1230 York Avenue New York, NY 10021-6399 Abstract Natural time-varying images possess significant temporal correlations when sampled frame by frame by the photoreceptors. These correlations persist even after retinal processing and hence, under natural activation conditions, the signal sent to the lateral geniculate nucleus is temporally redundant or inefficient. We explore the hypothesis that the LGN is concerned, among other things, with improving efficiency of visual representation through active temporal decorrelation of the retinal signal much in the same way that the retina improves efficiency by spatially decorrelating incoming images. Using some recently measured statistical properties of time-varying images, we predict the spatio-temporal receptive fields that achieve this decorrelation. It is shown that, because of neuronal nonlinearities, temporal decorrelation requires two response types, the {\it lagged} and {\it nonlagged}, just as spatial decorrelation requires {\it on} and {\it off} response types. The tuning and response properties of the predicted LGN cells compare quantitatively well with what is observed in recent physiological experiments. {Network: Computation in Neural Systems}{ Vol~6(2) pp~159-178} From omlinc@research.nj.nec.com Tue Jun 13 21:51:30 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 13 Jun 95 21:51:27 -0500; AA16331 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 13 Jun 95 21:51:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab20273; 13 Jun 95 18:36:20 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab20271; 13 Jun 95 18:25:57 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02872; 13 Jun 95 18:25:48 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa15883; 13 Jun 95 14:50:50 EDT Received: from zingo.nj.nec.com by CS.CMU.EDU id aa29439; 13 Jun 95 14:49:30 EDT Received: by zingo (940816.SGI.8.6.9/YDL1.4-910307.16) id OAA03163(zingo); Tue, 13 Jun 1995 14:47:26 -0400 Received: by arosa (5.52/cliff's joyful mailer #2) id AA00207(arosa); Tue, 13 Jun 95 14:47:26 EDT Date: Tue, 13 Jun 95 14:47:26 EDT From: Christian Omlin Message-Id: <9506131847.AA00207@arosa> To: connectionists@cs.cmu.edu Subject: Preprint Available - Knowledge Extraction The following technical report is available from the archive of the Computer Science Department, University of Maryland. URL: http://www.cs.umd.edu:80/TR/UMCP-CSD:CS-TR-3465 FTP: ftp.cs.umd.edu:/pub/papers/papers/3465/3465.ps.Z We welcome your comments. Christian Extraction of Rules from Discrete-Time Recurrent Neural Networks Revised Technical Report CS-TR-3465 and UMIACS-TR-95-54 University of Maryland, College Park, MD 20742 Christian W. Omlin and C. Lee Giles NEC Research Institute 4 Independence Way Princeton, N.J. 08540 USA E-mail: {omlinc,giles}@research.nj.nec.com ABSTRACT The extraction of symbolic knowledge from trained neural networks and the direct encoding of (partial) knowledge into networks prior to training are important issues. They allow the exchange of information between symbolic and connectionist knowledge representation. The focus of this paper is on the quality of the rules that are extracted from recurrent neural networks. Discrete-time recurrent neural networks can be trained to correctly classify strings of a regular language. Rules defining the learned grammar can be extracted from networks in the form of deterministic finite-state automata (DFA's) by applying clustering algorithms in the output space of recurrent state neurons. Our algorithm can extract different finite-state automata that are consistent with a training set from the same network. We compare the generalization performances of these different models and the trained network and we introduce a heuristic that permits us to choose among the consistent DFA's the model which best approximates the learned grammar. Keywords: Recurrent Neural Networks, Grammatical Inference, Regular Languages, Deterministic Finite-State Automata, Rule Extraction, Generalization Performance, Model Selection, Occam's Razor. From stokely@atax.eng.uab.edu Tue Jun 13 21:51:31 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Tue, 13 Jun 95 21:51:29 -0500; AA16336 Message-Id: <9506140251.AA17091@lucy.cs.wisc.edu> Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Tue, 13 Jun 95 21:51:27 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa20301; 13 Jun 95 18:51:06 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa20294; 13 Jun 95 18:40:16 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02902; 13 Jun 95 18:40:05 EDT Date: Mon, 12 Jun 1995 17:48:39 -0500 To: Connectionists@cs.cmu.edu From: Ernest Stokely Subject: Position in Biomedical Engineering Tenure Track Faculty Position -------------------------- The Department of Biomedical Engineering at the University of Alabama at Birmingham has an opening for a tenure-track faculty member. The opening is being filled as part of a Whitaker Foundation Special Opportunities Award for a training and research program in functional and structural imaging of the brain. Candidates are particularly invited in cross-disciplinary areas of neurosystems, biological neural networks, computational neurobiology, or other multidisciplinary areas that combine neurobiology and imaging. The person selected for this position will be expected to form active research collaborations with other units in the Medical Affairs part of the UAB campus. Candidates should have a Ph.D. degree in engineering or a related field, and must be a U.S. citizen or have permanent residency in the U.S. The search will be continued until the position is filled. UAB is an autonomous campus within the University of Alabama system. UAB faculty currently are involved in over $140 million of externally funded grants and contracts. A 4.1 Tesla clinical NMR facility for cardiovascular research, several other small-bore MR systems, a Philips Gyroscan system, and a team of research scientists and engineers working in various aspects of MR imaging and spectroscopy are housed only 200 meters from the School of Engineering. In addition, the brain imaging project will involve collaborations with members of the Neurobiology Center, as well as faculty members from the Departments of Neurology, Psychiatry, and Radiology. To apply send a letter of application, a current curriculum vitae, and three letters of reference to Dr. Ernest Stokely, Department of Biomedical Engineering, BEC 256, University of Alabama at Birmingham, Birmingham, Alabama 35294-4461. The University of Alabama at Birmingham is an equal opportunity, affirmative action employer, and encourages applications from qualified women and minorities. Ernest Stokely Chair, Department of Biomedical Engineering BEC 256 University of Alabama at Birmingham Birmingham, Alabama 35294-4461 Internet: stokely@atax.eng.uab.edu FAX: (205) 975-4919 Phone: (205) 934-8420 From terry@salk.edu Wed Jun 14 12:43:24 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Wed, 14 Jun 95 12:43:22 -0500; AA25003 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Wed, 14 Jun 95 12:43:20 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa20288; 13 Jun 95 18:44:12 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa20277; 13 Jun 95 18:26:50 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02879; 13 Jun 95 18:26:40 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa17317; 13 Jun 95 16:21:27 EDT Received: from helmholtz.salk.edu by CS.CMU.EDU id aa00541; 13 Jun 95 16:19:40 EDT Received: by salk.edu (4.1/SMI-4.1) id AA28440; Tue, 13 Jun 95 13:19:25 PDT Date: Tue, 13 Jun 95 13:19:25 PDT From: Terry Sejnowski Message-Id: <9506132019.AA28440@salk.edu> To: connectionists@cs.cmu.edu, terry@salk.edu Subject: Re: Neural Computation 7:4 Neural Computation Volume 7 Number 4 July 1995 Review: Hints Yaser Abu-Mostafa Articles: Topology and geometry of weight solutions in multi-layer networks Frans M. Coetzee and Virginia L. Stonick Letters: Time-skew Hebb rule in a nonisopotential neuron Barak A. Pearlmutter Synapse models for neural networks: From ion channel kinetics to multiplicative coefficient wij Francois Chapeau-Blondeau and Nicolas Chambet Generalization and analysis of the Lisberger-Sejnowski VOR model Ning Qian Stable adaptive control of robot manipulators using neural networks Robert M. Sanner and Jean-Jacques E. Slotine Modular and hybrid connectionist system for automatic speaker identification Younes Bennani Error estimation by series association for artificial neural network systems Keehoon Kim and Eric B. Bartlett Test error fluctuations in finite linear perceptrons D. Barber, D. Saad and P. Sollich Learning and extracting initial mealy automata with a modular neural network model Peter Tino and Jozef Sajda Dynamic cell structure learns perfectly topology preserving map Jorg Bruske and Gerald Sommer ----- ABSTRACTS - http://www-mitpress.mit.edu/ SUBSCRIPTIONS - 1995 - VOLUME 7 - BIMONTHLY (6 issues) ______ $40 Student and Retired ______ $68 Individual ______ $180 Institution Add $22 for postage and handling outside USA (+7% GST for Canada). (Back issues from Volumes 1-6 are regularly available for $28 each to institutions and $14 each for individuals Add $5 for postage per issue outside USA (+7% GST for Canada) MIT Press Journals, 55 Hayward Street, Cambridge, MA 02142. Tel: (617) 253-2889 FAX: (617) 258-6779 e-mail: hiscox@mitvma.mit.edu ----- From omlinc@research.nj.nec.com Wed Jun 14 22:26:31 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Wed, 14 Jun 95 22:26:28 -0500; AA00476 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Wed, 14 Jun 95 22:26:25 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa21687; 14 Jun 95 13:26:23 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa21685; 14 Jun 95 13:05:29 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa03600; 14 Jun 95 13:05:02 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa01452; 14 Jun 95 11:17:03 EDT Received: from zingo.nj.nec.com by RI.CMU.EDU id aa04276; 14 Jun 95 11:15:37 EDT Received: by zingo (940816.SGI.8.6.9/YDL1.4-910307.16) id LAA12969(zingo); Wed, 14 Jun 1995 11:13:24 -0400 Received: by arosa (5.52/cliff's joyful mailer #2) id AA02813(arosa); Wed, 14 Jun 95 11:13:23 EDT Date: Wed, 14 Jun 95 11:13:23 EDT From: Christian Omlin Message-Id: <9506141513.AA02813@arosa> To: connectionists@cs.cmu.edu Subject: Technical Report - Alternate Sites There seems to be a problem with accessing the technical report Extraction of Rules from Discrete-Time Recurrent Neural Networks by Christian W. Omlin and C. Lee Giles from the sites http://www.cs.umd.edu:80/TR/UMCP-CSD:CS-TR-3465 ftp.cs.umd.edu:/pub/papers/papers/3465/3465.ps.Z The above technical report can now be accessed either through my home page at http://www.neci.nj.nec.com/homepages/omlin/omlin.html or via ftp from ftp.nj.nec.com /pub/omlinc/rule_extraction.ps.Z I apologize for the inconvenience. Christian From phkywong@uxmail.ust.hk Thu Jun 15 13:25:45 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 15 Jun 95 13:25:43 -0500; AA09413 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 15 Jun 95 13:25:41 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa23101; 15 Jun 95 12:26:31 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa23099; 15 Jun 95 12:14:43 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa04492; 15 Jun 95 12:14:31 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa18519; 15 Jun 95 5:37:30 EDT Received: from uxmail.ust.hk by RI.CMU.EDU id aa07660; 15 Jun 95 5:36:13 EDT Received: from phsu2.ust.hk by uxmail.ust.hk id <18918-1>; Thu, 15 Jun 1995 17:34:24 +0800 From: "Dr. Michael Wong" To: connectionists@cs.cmu.edu Subject: Paper on Neural Network Classification Available Cc: phhclau@uxmail.ust.hk Message-Id: <95Jun15.173424+0800_hkt.18918-1+162@uxmail.ust.hk> Date: Thu, 15 Jun 1995 17:34:24 +0800 FTP-host: physics.ust.hk FTP-file: pub/kymwong/nips95.ps.gz The following paper, submitted to the Theory session of NIPS-95, is now available via anonymous FTP. (8 pages long) ============================================================================ Neural Network Classification of Non-Uniform Data K. Y. Michael Wong and H. C.Lau, Department of Physics, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong. E-mail address: phkywong@usthk.ust.hk, phhclau@usthk.ust.hk ABSTRACT We consider a model of non-uniform data, which resembles typical data for system faults in diagnostic classification tasks. Pre-processing the data for feature extraction and dimensionality reduction improves the performance of neural network classifiers, in terms of the number of training examples required for good generalization. This result supports the use of hybrid expert systems in which feature extraction techniques such as classification trees are used to build a pre-processing layer for neural network classifiers. ============================================================================ FTP instructions: unix> ftp physics.ust.hk Name: anonymous Password: your full email address ftp> cd pub/kymwong ftp> get nips95.ps.gz ftp> quit unix> gunzip nips95.ps.gz unix> lpr nips95.ps From djf3@cornell.edu Thu Jun 15 13:25:48 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 15 Jun 95 13:25:46 -0500; AA09419 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 15 Jun 95 13:25:43 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa23116; 15 Jun 95 12:34:08 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa23103; 15 Jun 95 12:15:33 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa04500; 15 Jun 95 12:15:12 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa24065; 15 Jun 95 12:05:41 EDT Received: from POSTOFFICE.MAIL.CORNELL.EDU by RI.CMU.EDU id aa08612; 15 Jun 95 12:04:51 EDT Received: from [128.253.74.208] (COMP208.PSYCH.CORNELL.EDU [128.253.74.208]) by postoffice.mail.cornell.edu (8.6.9/8.6.9) with SMTP id MAA12338 for ; Thu, 15 Jun 1995 12:04:47 -0400 Date: Thu, 15 Jun 1995 12:04:47 -0400 X-Sender: djf3@postoffice.mail.cornell.edu Message-Id: Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" To: Connectionists@cs.cmu.edu From: David Field Subject: Big brains conference There remains a limited number of openings for people wishing to attend this year's Cornell Symposium. A list of speakers and abstracts of talks can be found on our World Wide Web page. The URL is http://comp9.psych.cornell.edu/Psychology/big-brains.html or http://redwood.psych.cornell.edu/big-brains.html Cornell University Summer Symposium 1995: Big Brains June 23-26 Co-organizers: Barbara Finlay and David Field Many forces encourage and constrain the development of large brains, and large brains assemble themselves into new architectures that reflect these forces. Big brains are presumably selected for better and more efficient perception, cognition and behavior: how is selection for behavior translated into structure? Organismal and developmental constraints on selection for increased brain size are numerous: energetic requirements of the developing fetus, linkage of early developmental events, body conformation factors like pelvis size, social structure of the species and the mature brain's energetic requirements are all examples of forces which influence brain size and conformation. We now know a number of essential facts about how distribution of connectivity, modularity and the nature of functional specialization change as brains get large. Current work on computational architecture of neural nets has revealed strategies that work optimally for either small or large assemblies of units, and principles of organization that emerge only in larger assemblies. Using "big brains" as a focal point, this conference draws together researchers who work at all these levels of analysis to understand more of how our large brain has come to be. From jlm@crab.psy.cmu.edu Thu Jun 15 22:41:02 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Thu, 15 Jun 95 22:40:59 -0500; AA13107 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Thu, 15 Jun 95 22:40:57 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa23632; 15 Jun 95 20:34:21 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa23624; 15 Jun 95 20:18:18 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa04647; 15 Jun 95 20:18:06 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa27789; 15 Jun 95 16:04:45 EDT Received: from ANDREW.CMU.EDU by EDRC.CMU.EDU id aa09053; 15 Jun 95 16:04:04 EDT Received: from crab.psy.cmu.edu.psy.cmu.edu (CRAB.PSY.CMU.EDU [128.2.248.139]) by andrew.cmu.edu (8.6.12/8.6.12) with SMTP id QAA11294 for ; Thu, 15 Jun 1995 16:04:02 -0400 Received: by crab.psy.cmu.edu.psy.cmu.edu (4.1/SMI-4.1) id AA25171; Thu, 15 Jun 95 16:04:01 EDT Date: Thu, 15 Jun 95 16:04:01 EDT From: "James L. McClelland" Message-Id: <9506152004.AA25171@crab.psy.cmu.edu.psy.cmu.edu> To: connectionists@cs.cmu.edu Subject: ANNOUNCING THE PDP++ SIMULATOR ANNOUNCING: The PDP++ Software Authors: Randall C. O'Reilly, Chadley K. Dawson, and James L. McClelland The PDP++ software is a new neural-network simulation system written in C++. It represents the next generation of the PDP software released with the McClelland and Rumelhart "Explorations in Parallel Distributed Processing Handbook", MIT Press, 1987. It is easy enough for novice users, but very powerful and flexible for research use. The current version is 1.0 beta (1.0b). It has been used and tested locally fairly extensively during development, but this is the first general release. The software can be obtained by anonymous ftp from: Anonymous FTP Site: hydra.psy.cmu.edu/pub/pdp++ For more information, see our web page: WWW Page: http://www.cs.cmu.edu/Web/Groups/CNBC/PDP++/PDP++.html There is a 250 page (printed) manual and an HTML version available on-line at the above address. Software Features: ================== o Full Graphical User Interface (GUI) based on the InterViews toolkit. Allows user-selected "look and feel". o Network Viewer shows network architecture and processing in real- time, allows network to be constructed with simple point-and-click actions. o Training and testing data can be graphed on-line and network state can be displayed over time numerically or using a wide range of color or size-based graphical representations. o Environment Viewer shows training patterns using color or size-based graphical representations. o Flexible object-oriented design allows mix-and-match simulation construction and easy extension by deriving new object types from existing ones. o Built-in 'CSS' scripting language uses C++ syntax, allows full access to simulation object data and functions. Transition between script code and compiled code is simplified since both are C++. Script has command-line completion, source-level debugger, and provides standard C/C++ library functions and objects. o Scripts can control processing, generate training and testing patterns, automate routine tasks, etc. o Scripts can be generated from GUI actions, and the user can create GUI interfaces from script objects to extend and customize the simulation environment. Supported Algorithms: ===================== o Feedforward and recurrent error backpropagation. Recurrent BP includes continuous, real-time models, and Almeida-Pineda. o Constraint satisfaction algorithms and associated learning algorithms including Boltzmann Machine, Hopfield models, mean-field networks (DBM), Interactive Activation and Competition (IAC), and continuous stochastic networks. o Self-organizing learning including Competitive Learning, Soft Competitive Learning, simple Hebbian, and Self-organizing Maps ("Kohonen Nets"). The Fine Print: =============== PDP++ is copyrighted and cannot be sold or distributed by anyone other than the copyright holders. However, the full source code is freely available, and the user is granted full permission to modify, copy, and use it. See our web page for details. The software runs on Unix workstations under XWindows. It requires a minimum of 16 Meg of RAM, and 32 Meg is preferable. It has been developed and tested on Sun Sparc's under SunOs 4.1.3, HP 7xx under HP-UX 9.x, and SGI Irix 5.3. Statically linked binaries are available for these machines. Other machine types will require compiling from the source. Cfront 3.x and g++ 2.6.3 are supported C++ compilers. The GUI in PDP++ is based on the InterViews toolkit, version 3.2a. However, we had to patch it to get it to work. We distribute pre-compiled libraries containing these patches for the above architectures. For architectures other than those above, you will have to apply our patches to InterViews before compiling. The basic GUI and script technology in PDP++ is based on a type-scanning system called TypeAccess which interfaces with the CSS script language to provide a virtually automatic interface mechanism. While these were developed for PDP++, they can easily be used for any kind of application, and CSS is available as a stand-alone executable for use like Perl or TCL. The binary-only distribution requires about 54 Meg of disk space, since we have been unable to get shared libraries to work with C++ on the above platforms. Each simulation executable is around 8-12 Meg in size, and there are 3 of these (bp++, cs++, so++), plus the CSS and 'maketa' executables. The compiled source-code distribution takes about 115 Meg (but only around 16 Meg before compiling). For more information on the details of the software, see our web page. From dhw@santafe.edu Fri Jun 16 07:53:17 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 16 Jun 95 07:53:15 -0500; AA16815 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Fri, 16 Jun 95 07:53:13 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa23619; 15 Jun 95 20:27:01 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa23617; 15 Jun 95 20:15:52 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa04642; 15 Jun 95 20:15:19 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aj29946; 15 Jun 95 19:18:33 EDT Received: from sfi.santafe.edu by CS.CMU.EDU id aa20534; 15 Jun 95 18:00:59 EDT Received: from pojoaque (pojoaque.santafe.edu) by sfi.santafe.edu (4.1/SMI-4.1) id AA22307; Thu, 15 Jun 95 16:01:35 MDT Date: Thu, 15 Jun 95 16:01:35 MDT From: David Wolpert Message-Id: <9506152201.AA22307@sfi.santafe.edu> To: Connectionists@cs.cmu.edu Subject: Paper announcement NEW PAPER ANNOUNCEMENT. *** Some Results Concerning Off-Training-Set and IID Error for the Gibbs and the Bayes Optimal Generalizers by David H. Wolpert, Emanuel Knill, Tal Grossman Abstract: In this paper we analyze the average behavior of the Bayes-optimal and Gibbs learning algorithms. We do this both for off-training-set error and conventional IID error (for which test sets overlap with training sets). For the IID case we provide a major extension to one of the better known results of \cite{haussler}. We also show that expected IID test set error is a non-increasing function of training set size for either algorithm. On the other hand, as we show, the expected off training-set error for both learning algorithms can increase with training set size, for non-uniform sampling distributions. We characterize what relationship the sampling distribution must have with the prior for such an increase. We show in particular that for uniform sampling distributions and either algorithm, the expected off-training set error is a non-increasing function of training set size. For uniform sampling distributions, we also characterize the priors for which the expected error of the Bayes-optimal algorithm stays constant. In addition we show that for the Bayes-optimal algorithm, expected off-training-set error can increase with training set size when the target function is fixed, but if and only if the expected error averaged over all targets decreases with training set size. Our results hold for arbitrary noise and arbitrary loss functions. *** To retrieve this file, anonymous ftp to ftp.santafe.edu. Go to pub/dhw_ftp. Compressed postscript of the file is called OTS.BO.Gibbs.ps.Z. From furuhashi@nuee.nagoya-u.ac.jp Fri Jun 16 19:32:36 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 16 Jun 95 19:32:34 -0500; AA21542 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Fri, 16 Jun 95 19:32:32 -0500 Received: by TELNET-1.SRV.CS.CMU.EDU id ab24910; 16 Jun 95 17:16:19 EDT Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa24878; 16 Jun 95 16:42:21 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa24876; 16 Jun 95 16:24:50 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05571; 16 Jun 95 16:24:39 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa05285; 16 Jun 95 4:22:55 EDT Return-Path: Received: from [133.6.107.82] (andromeda.bioele.nuee.nagoya-u.ac.jp) by gemini.bioele.nuee.nagoya-u.ac.jp (4.1/3.3W9-smtp) id AA19245; Fri, 16 Jun 95 16:54:54 JST Message-Id: <9506160754.AA19245@gemini.bioele.nuee.nagoya-u.ac.jp> Date: Fri, 16 Jun 1995 16:54:55 +0900 To: Connectionists@cs.cmu.edu From: furuhashi@nuee.nagoya-u.ac.jp X-Sender: furu@gemini.bioele.nuee.nagoya-u.ac.jp Subject: Call for Papers of WWW'95 Mime-Version: 1.0 Content-Type: text/plain; charset=iso-2022-jp X-Mailer: Eudora-J(1.3.7-J12) CALL FOR PAPERS 1995 IEEE/Nagoya University World Wisepersons Workshop (WWW'95) ON FUZZY LOGIC AND NEURAL NETWORKS/EVOLUTIONARY COMPUTATION November 14 and 15, 1995 Rubrum Ohzan Chikusa-ku, Nagoya, JAPAN Sponsored by Nagoya University Co-sponsored by IEEE Industrial Electronics Society Technically Co-sponsored by IEEE Robotics and Automation Society International Fuzzy Systems Association Japan Society for Fuzzy Theory and Systems North American Fuzzy Information Processing Society Society of Instrument and Control Engineers Robotics Society of Japan There are growing interests in combination technologies of fuzzy logic and neural networks, fuzzy logic and evolutionary computation for acquisition of experts' knowledge, modeling of nonlinear systems, realizing complex adaptive systems. The goal of the 1995 IEEE/Nagoya University WWW on Fuzzy Logic and Neural Networks/Evolutionary Computation is to give its attendees opportunities to exchange information and ideas on various aspects of the Combination Technologies and to stimulate and inspire pioneering works in this area. To keep the quality of these workshop high, only a limited number of people are accepted as participants of the workshops. The papers presented at the workshop are planned to be edited and published from Springer-Verlag. For speakers of excellent papers, partial financial assistance of travel expense as well as lodging fee in Nagoya will be provided by the steering committee of WWW'95. TOPICS: Combination of Fuzzy Logic and Neural Networks, Combination of Fuzzy Logic and Evolutionary Computation, Learning and Adaptation, Knowledge Acquisition, Modeling, Human Machine Interface IMPORTANT DATES: Submission of Abstracts of Papers : June 30, 1995 Acceptance Notification : Aug. 31, 1995 Final Manuscript : Sept. 30, 1995 Abstracts should be type-written in English within 4 pages of A4 size or Letter sized sheet. Use Times or one of the similar typefaces. The size of the letters should be 10 points or larger. All correspondence and submission of papers should be sent to Takeshi Furuhashi, General Chair Dept. of Information Electronics, Nagoya University Furo-cho, Chikusa-ku, Nagoya 464-01, JAPAN TEL: +81-52-789-2792, FAX: +81-52-789-3166 E mail: furuhashi@nuee.nagoya-u.ac.jp IEEE/Nagoya University WWW: IEEE/Nagoya University WWW (World Wiseperson Workshop) is a series of workshops sponsored by Nagoya University and co-sponsored by IEEE Industrial Electronics Society. City of Nagoya, located two hours away from Tokyo, has many electro-mechanical industries in its surroundings such as Mitsubishi, TOYOTA, and their allied companies. Nagoya is a mecca of robotics industries, machine industries and aerospace industries in Japan. The series of workshops will give its attendees opportunities to exchange information on advanced sciences and technologies and to visit industries and research institutes in this area. WORKSHOP ORGANIZATION Honorary Chair: Masanobu Hasatani (Dean, School of Engineering, Nagoya University) General Chair: Takeshi Furuhashi (Nagoya University) Advisory Committee: Chair: Toshio Fukuda (Nagoya University) Toshio Goto (Nagoya University) Fumio Harashima (University of Tokyo) Richard D. Klafter (Temple University) C.S. George Lee (Purdue University) Hiroyasu Nomura (Nagoya University) Shigeru Okuma (Nagoya University) Yoshiki Uchikawa (Nagoya University) Steering Committee: S.Abe (Hitach Ltd.) K.Aoki (Toyota Motor Corporation) T.Aoki (Nagoya Municipal Industrial Res. Inst.) M.Arao (OMRON Corporation) Y.Dote (Muroran Institute of Technology) M.Fathi (University of Dortmund) M.Gen (Ashikaga Institute of Technology) H.Hashimoto (Univ. of Tokyo) I.Hayashi (Hannann Universtity) M.Hiller (Gerhard-Mercator-Universit閣) H.Honda (Oki Technosystems Laboratory, Inc.) H.Ichihashi (University of Osaka Prefecture) T.Iokibe (Meidensha Corporation) H.Ishibuchi (University of Osaka Prefecture) A.Ishiguro (Nagoya University) O.Ito (Fuji Electric Corporate Res.& Develop., Ltd.) N.Kasabov (University of Otago) R.Katayama (Sanyo Electric Co., Ltd.) E.Khan (National Semiconductor) H.Kitano (Sony CSL) K.M.Lee (KAIST) M.A.Lee (University of California, Berkeley) Y.Maeda (Osaka Electro-Communication Univ.) T.Muramatsu (Nippon Steel Corporation) S.Nakanishi (Tokai University) T.Nomura (SHARP Corporation) H.Ohno (Toyota Central Res.& Develop.Lab., Inc.) M.Sano (Hiroshima City University) M.Sakawa (Hiroshima University) T.Shibata (MEL, MITI) H.Shiizuka (Kogakuin University) K.Shimohara (ATR) K.Tanaka (Kanazawa University) T.Yamada (NTT) T.Yamaguchi (Utsunomiya University) N.Wakami (Matsushita Electric Industrial Co., Ltd.) J.Watada (Osaka Institute of Technology) K.Watanabe (Saga University) --------------------------------------------------- Takeshi Furuhashi, Assoc. Professor Dept. of Information Electronics, Nagoya University Furo-cho, Chikusa-ku, Nagoya 464-01, Japan Tel.+81-52-789-2792, Fax.+81-52-789-3166 --------------------------------------------------- From juergen@idsia.ch Fri Jun 16 19:54:24 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Fri, 16 Jun 95 19:54:22 -0500; AA21604 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Fri, 16 Jun 95 19:54:20 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa24893; 16 Jun 95 16:52:10 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa24882; 16 Jun 95 16:25:47 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05576; 16 Jun 95 16:24:48 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa05548; 16 Jun 95 5:01:20 EDT Received: from [146.228.10.15] by RI.CMU.EDU id aa11605; 16 Jun 95 5:00:44 EDT Received: from fava.idsia.ch by chsun.eunet.ch (8.6.10/1.34) id LAA18034; Fri, 16 Jun 1995 11:02:18 +0200 Received: from kraut.idsia.ch by fava.idsia.ch (4.1/SMI-4.1) id AA13539; Fri, 16 Jun 95 10:58:52 +0200 Date: Fri, 16 Jun 95 10:58:52 +0200 From: Juergen Schmidhuber Message-Id: <9506160858.AA13539@fava.idsia.ch> To: connectionists@cs.cmu.edu Subject: new IDSIA papers 3 new IDSIA publications available. Click at http://www.idsia.ch or use ftp: FTP-host: fava.idsia.ch (192.132.252.1) FTP-filenames: /pub/papers/ml95.kolmogorov.ps.gz 9 pages /pub/papers/ml95.antq.ps.gz 9 pages /pub/papers/iwann95.invertible.ps.gz 8 pages (use gunzip to uncompress) ___________________________________________________________________ DISCOVERING SOLUTIONS WITH LOW KOLMOGOROV COMPLEXITY AND HIGH GENERALIZATION CAPABILITY Juergen Schmidhuber, IDSIA To appear in Machine Learning: Proc. 12th int. conf., 1995. This paper reviews basic concepts of Kolmogorov complexity theory relevant to machine learning. It shows how a derivate of Levin's universal search algorithm can be used to discover neural nets with low Levin complexity, low Kolmogorov complexity, and high generalization capability. At least with certain toy problems where it is computationally feasible, the method can lead to generalization results unmatchable by previous neural net algorithms. The final section addresses problems with incremental learning situations. ANT-Q Luca Gambardella, IDSIA Marco Dorigo, IDSIA To appear in Machine Learning: Proc. 12th int. conf., 1995. We introduce Ant-Q, a family of algorithms which share many similarities with Q-learning (Watkins, 1989). Ant-Q is a generalization of the ``ant system'' (AS --- Dorigo, 1992; Dorigo, Maniezzo and Colorni, 1996), a distributed algorithm for combinatorial optimization based on the ant colony metaphor. In applications to symmetric traveling salesman problems (TSPs), we demonstrate (1) that some Ant-Q instances outperform AS, and (2) that Ant-Q compares favorably with other heuristic approaches based on neural nets or local search. Finally, we apply Ant-Q to some difficult asymmetric TSP's and obtain excellent results: Ant-Q finds solutions of a quality which usually can be found only by highly specialized algorithms. LEARNING THE VISUOMOTOR COORDINATION OF A MOBILE ROBOT BY USING THE INVERTIBLE KOHONEN MAP Cristina Versino, IDSIA Luca Gambardella, IDSIA In Proc. International Workshop on Artificial Neural Networks 1995. This paper is based on the insight that the Extended Kohonen Map (EKM) is naturally invertible: given an input pattern, the network output is generated by competition among the neuron fan-in weight vectors (conventional ``forward mode''). Viceversa, given an output value, a corresponding input pattern can be obtained by competition among the neuron fan-out weight vectors (unconventional ``backward mode''). This invertibility property makes EKM worth considering for sensorimotor modeling. We present an experiment concerning visuomotor coordination of a simple mobile robot. ``Learning by doing'' creates a sensorimotor model: pairs are collected by observing the robot's behavior. These pairs are used for estimating the model's parameters. Training the network on the robot's direct kinematics (forward mode), one simultaneously obtains a solution to the inverse kinematics problem (backward mode). The experiment has been performed both in a simulation and by using a real robot. ___________________________________________________________________ Related and other papers in http://www.idsia.ch Comments welcome. Juergen Schmidhuber Research Director IDSIA, Corso Elvezia 36 6900-Lugano, Switzerland juergen@idsia.ch From harnad@ecs.soton.ac.uk Sat Jun 17 17:01:02 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 17 Jun 95 17:00:58 -0500; AA26747 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sat, 17 Jun 95 17:00:55 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa26241; 17 Jun 95 12:08:31 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa26239; 17 Jun 95 11:59:10 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa06496; 17 Jun 95 11:58:42 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa24010; 17 Jun 95 11:29:45 EDT Received: from beech.soton.ac.uk by CS.CMU.EDU id aa01671; 17 Jun 95 11:29:06 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 QAA19952; Sat, 17 Jun 1995 16:27:22 +0100 Received: from louis.ecs.soton.ac.uk by bright.ecs.soton.ac.uk; Sat, 17 Jun 95 16:26:40 BST From: Stevan Harnad Received: from cogsci by louis.ecs.soton.ac.uk; Sat, 17 Jun 95 16:26:38 BST Date: Sat, 17 Jun 95 16:26:53 +0100 Message-Id: <23611.9506171526@cogsci> To: PSYCOLOQUY Subject: Memory: BBS Call for Commentators Cc: PHILOS-L@liverpool.ac.uk, cogni-publication@univ-lyon1.fr, Soc Phil Psych Below is the abstract of a forthcoming target article on: MEMORY METAPHORS by A. Koriat and M. Goldsmith This article has been accepted for publication in Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal providing Open Peer Commentary on important and controversial current research in the biobehavioral and cognitive sciences. Commentators must be current BBS Associates or nominated by a current BBS Associate. To be considered as a commentator for this article, to suggest other appropriate commentators, or for information about how to become a BBS Associate, please send email to: bbs@ecs.soton.ac.uk or write to: Behavioral and Brain Sciences Department of Psychology University of Southampton Highfield, Southampton SO17 1BJ UNITED KINGDOM http://cogsci.ecs.soton.ac.uk/~harnad/bbs.html gopher://gopher.princeton.edu:70/11/.libraries/.pujournals ftp://ftp.princeton.edu/pub/harnad/BBS To help us put together a balanced list of commentators, please give some indication of the aspects of the topic on which you would bring your areas of expertise to bear if you were selected as a commentator. An electronic draft of the full text is available for inspection by anonymous ftp (or gopher or world-wide-web) according to the instructions that follow after the abstract. ____________________________________________________________________ MEMORY METAPHORS AND THE LABORATORY/REAL-LIFE CONTROVERSY: CORRESPONDENCE VERSUS STOREHOUSE VIEWS OF MEMORY Asher Koriat and Morris Goldsmith Department of Psychology University of Haifa Haifa, Israel rsps301@uvm.haifa.ac.il KEYWORDS: accuracy, assessment, capacity ecological validity, intentionality, memory, metamemory, metaphors, monitoring, representation, storehouse, subject control. ABSTRACT: The study of memory is witnessing a spirited clash between proponents of traditional laboratory research and those advocating a more naturalistic approach to the study of "everyday" memory. The debate has generally centered on the "what" (content), "where" (context), and "how" (methods) of memory research. In the present target article, we argue that this controversy discloses a further, more fundamental breach between two underlying memory metaphors, each having distinct implications for memory theory and assessment: Whereas traditional memory research has been dominated by the storehouse metaphor, leading to a focus on the quantity of items remaining in store, the recent wave of everyday memory research discloses a shift towards a correspondence metaphor, focusing on the accuracy or faithfulness of memory in representing past events. Our analysis shows the correspondence metaphor to call for a research approach which differs from the traditional approach in important respects: in emphasizing the intentional-representational function of memory, in addressing the wholistic and graded aspects of memory correspondence, in taking an output-bound assessment perspective, and in allowing more room for the operation of subject-controlled metamemory processes and motivational factors. This analysis can help tie together some of the what, where, and how aspects of the everyday-laboratory controversy. More importantly, in explicating the unique metatheoretical foundation of the accuracy-oriented approach to memory, our aim is to promote a more effective exploitation of the correspondence metaphor in both naturalistic and laboratory research contexts. -------------------------------------------------------------- To help you decide whether you would be an appropriate commentator for this article, an electronic draft is retrievable by anonymous ftp from ftp.princeton.edu according to the instructions below (the filename is bbs.koriat). Please do not prepare a commentary on this draft. Just let us know, after having inspected it, what relevant expertise you feel you would bring to bear on what aspect of the article. ------------------------------------------------------------- These files are also on the World Wide Web and the easiest way to retrieve them is with Netscape, Mosaic, gopher, archie, veronica, etc. Here are some of the URLs you can use to get to the BBS Archive: http://www.princeton.edu/~harnad/bbs.html http://cogsci.ecs.soton.ac.uk/~harnad/bbs.html gopher://gopher.princeton.edu:70/11/.libraries/.pujournals ftp://ftp.princeton.edu/pub/harnad/BBS/bbs.koriat ftp://cogsci.ecs.soton.ac.uk/pub/harnad/BBS/bbs.koriat To retrieve a file by ftp from an Internet site, type either: ftp ftp.princeton.edu or ftp 128.112.128.1 When you are asked for your login, type: anonymous Enter password as queried (your password is your actual userid: yourlogin@yourhost.whatever.whatever - be sure to include the "@") cd /pub/harnad/BBS To show the available files, type: ls Next, retrieve the file you want with (for example): get bbs.koriat When you have the file(s) you want, type: quit ---------- Where the above procedure is not available there are two fileservers: ftpmail@decwrl.dec.com and bitftp@pucc.bitnet that will do the transfer for you. To one or the other of them, send the following one line message: help for instructions (which will be similar to the above, but will be in the form of a series of lines in an email message that ftpmail or bitftp will then execute for you). ------------------------------------------------------------- From harnad@ecs.soton.ac.uk Sat Jun 17 20:09:24 1995 Received: from lucy.cs.wisc.edu by sea.cs.wisc.edu; Sat, 17 Jun 95 20:09:14 -0500; AA27069 Received: from TELNET-1.SRV.CS.CMU.EDU by lucy.cs.wisc.edu; Sat, 17 Jun 95 20:09:12 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab26241; 17 Jun 95 12:09:49 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab26239; 17 Jun 95 11:59:12 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa06501; 17 Jun 95 11:58:53 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa24128; 17 Jun 95 11:49:05 EDT Received: from beech.soton.ac.uk by EDRC.CMU.EDU id aa16265; 17 Jun 95 11:48:26 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 QAA20393; Sat, 17 Jun 1995 16:45:26 +0100 Received: from louis.ecs.soton.ac.uk by bright.ecs.soton.ac.uk; Sat, 17 Jun 95 16:44:44 BST From: Stevan Harnad Received: from cogsci by louis.ecs.soton.ac.uk; Sat, 17 Jun 95 16:44:42 BST Date: Sat, 17 Jun 95 16:44:57 +0100 Message-Id: <23748.9506171544@cogsci> To: PSYCOLOQUY Subject: EEG Dynamics: BBS Call for Commentators Cc: cogneuro@ptolemy-ethernet.arc.nasa.gov, connectionists@cs.cmu.edu, neuro1-l@uicvm.bitnet, neuromotor-control@ai.mit.edu Below is the abstract of a forthcoming target article on: BRAIN DYNAMICS, EEG & NEURAL NETS by JJ Wright & DTJ Liley This article has been accepted for publication in Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal providing Open Peer Commentary on important and controversial current research in the biobehavioral and cognitive sciences. Commentators must be current BBS Associates or nominated by a current BBS Associate. To be considered as a commentator for this article, to suggest other appropriate commentators, or for information about how to become a BBS Associate, please send email to: bbs@ecs.soton.ac.uk or write to: Behavioral and Brain Sciences Department of Psychology University of Southampton Highfield, Southampton SO17 1BJ UNITED KINGDOM http://cogsci.ecs.soton.ac.uk/~harnad/bbs.html gopher://gopher.princeton.edu:70/11/.libraries/.pujournals ftp://ftp.princeton.edu/pub/harnad/BBS To help us put together a balanced list of commentators, please give some indication of the aspects of the topic on which you would bring your areas of expertise to bear if you were selected as a commentator. An electronic draft of the full text is available for inspection by anonymous ftp (or gopher or world-wide-web) according to the instructions that follow after the abstract. ____________________________________________________________________ DYNAMICS OF THE BRAIN AT GLOBAL AND MICROSCOPIC SCALES: NEURAL NETWORKS AND THE EEG. J.J. Wright and D.T.J. Liley Mental Health Research Institute Parkville Victoria 3052, Australia jjw@cortex.mhri.edu.au Swinburne Center for Applied Neuroscience Hawthorne, Victoria 3122 Melbourne, Australia KEYWORDS: chaos, EEG simulation, electrocorticogram, neocortex, network symmetry, neurodynamics. ABSTRACT: There is some complementarity of models for the origin of the electroencephalogram (EEG), and neural network models for information storage in brain-like systems. From the EEG models of Freeman, Nunez, and the author's group, we argue that the wave-like processes revealed in the EEG exhibit linear and near-equilibrium dynamics at macroscopic scale, despite extremely nonlinear, probably chaotic, dynamics at microscopic scale. Simulations of cortical neuronal interactions at global and microscopic scales are then presented. The simulations depend on anatomical and physiological estimates of synaptic densities, coupling symmetries, synaptic gain, dendritic time constants and axonal delays. It is shown that the frequency content, wave velocities, frequency/wavenumber spectra and response to cortical activation of the electrocorticogram (ECoG) can be reproduced by a "lumped" simulation treating small cortical areas as single functional units. The corresponding cellular neural network simulation has properties which include those of attractor neural networks proposed by Amit, and Paresi. Within the simulations at both scales, sharp transitions occur between low and high cell firing rates. These transitions may form a basis for neural interactions across scale. To maintain overall cortical dynamics in the normal low firing-rate range, interactions between the cortex and subcortical systems are required to prevent runaway global excitation. Thus the interaction of cortex and subcortex via cortico-striatal and related pathways, may partly regulate global dynamics by a principle analogous to adiabatic control of artificial neural networks -------------------------------------------------------------- To help you decide whether you would be an appropriate commentator for this article, an electronic draft is retrievable by anonymous ftp from ftp.princeton.edu according to the instructions below (the filename is bbs.wright). Please do not prepare a commentary on this draft. Just let us know, after having inspected it, what relevant expertise you feel you would bring to bear on what aspect of the article. ------------------------------------------------------------- These files are also on the World Wide Web and the easiest way to retrieve them is with Netscape, Mosaic, gopher, archie, veronica, etc. Here are some of the URLs you can use to get to the BBS Archive: http://www.princeton.edu/~harnad/bbs.html http://cogsci.ecs.soton.ac.uk/~harnad/bbs.html gopher://gopher.princeton.edu:70/11/.libraries/.pujournals ftp://ftp.princeton.edu/pub/harnad/BBS/bbs.wright ftp://cogsci.ecs.soton.ac.uk/pub/harnad/BBS/bbs.wright To retrieve a file by ftp from an Internet site, type either: ftp ftp.princeton.edu or ftp 128.112.128.1 When you are asked for your login, type: anonymous Enter password as queried (your password is your actual userid: yourlogin@yourhost.whatever.whatever - be sure to include the "@") cd /pub/harnad/BBS To show the available files, type: ls Next, retrieve the file you want with (for example): get bbs.wright When you have the file(s) you want, type: quit ---------- Where the above procedure is not available there are two fileservers: ftpmail@decwrl.dec.com and bitftp@pucc.bitnet that will do the transfer for you. To one or the other of them, send the following one line message: help for instructions (which will be similar to the above, but will be in the form of a series of lines in an email message that ftpmail or bitftp will then execute for you). -------------------------------------------------------------