====================================================================== From: AARON SLOMAN Conference: 1252 , comp.ai To: ALL Message: 252 Reply To: 0 Subj: Re: The concept of inform Date: 06/01/95 Time: 20:44 ---------------------------------------------------------------------- ÿ@FROM :A.Sloman@cs.bham.ac.uk N ÿ@SUBJECT:Re: The concept of information N ÿ@UMSGID :<3ql8r5$hvc@percy.cs.bham.ac.uk> N ÿ@UNEWSGR:01comp.ai,comp.ai.philosophy N From: A.Sloman@cs.bham.ac.uk (Aaron Sloman) Newsgroups: comp.ai,comp.ai.philosophy Subject: Re: The concept of information Date: 1 Jun 1995 20:44:21 GMT Message-ID: <3ql8r5$hvc@percy.cs.bham.ac.uk> References:Xref: uunet comp.ai:30366 comp.ai.philosophy:28701 [I have added comp.ai.philosophy to the Newsgroups line.] theunissen@psych.kun.nl (Theo Theunissen) writes: > Date: Tue, 30 May 1995 20:38:36 +0100 > Organization: KUN > > In these days of computers, communication is a very intriguing but never > heard qeustion after the concept of information as a metaphysical > category. > We are are very curious if any one else. I don't know if it's an example of what you are talking about but I have a paper arguing that there is a (non-syntactic) concept of information which is used by (for example) software engineers, and is more fundamental than Newell's "Knowledge Level" or Dennett's "Intentional Stance". This concept of information is not essentially connected with communication between agents, as it can be applied to processes that occur within an agent (i.e. internal mechanisms acquire, store, manipulate and use information without necessarily involving communication with other agents -- but you could call it "self-communication". However some information essentially involves external objects, e.g. reference to the Eiffel Tower cannot be based entirely on the states of internal information processing mechanisms). I claim that the information level (which is close to Dennett's "Design Stance", and is very familiar to engineers even if they do not normally discuss its metaphysical significance!) provides a basis on which to consider architectures within which mental concepts can be defined. I.e. mental states, processes, capabilities, can be defined in terms of states and processes that information processing architectures can generate. So, mental concepts (analogous to "belief", "desire", etc.) are based on the design stance, not the intentional stance nor Newell's knowledge level. The phenomena that occur at the information level are implemented in physical processes, but are emergent in the sense that: a. the concepts required for describing them are not definable in terms of concepts of physics; b. the laws governing the virtual machines that operate at the information level are not derivable from laws of physics. E.g. the information processing rules can be changed without changing the laws of physics (but not without changing the implementation in some way); c. there need not be any simple (let alone one to one) correlations between events at the information processing level and physical events, or between structures at the two levels; d. any particular information level system may be implemented in very different physical machines (this is similar to point (c)). My ideas on this are still only vague, intuitive and incomplete and I welcome suggestions for correction and improvement. One example of the difference between the information processing level and the intentional or knowledge level described by Dennett and Newell is that the information processing level does not depend on any presumption of rationality. This is important, because I don't think intelligence in a resource-bounded agent requires rationality. In fact the requirement for total rationality leads to all sorts of contradictions and paradoxes that have bedevilled philosophical discussions of the nature of mind and knowledge for centuries. The paper attempting to develop these ideas is: A.Sloman, Semantics in an intelligent control system, in Philosophical Transactions of the Royal Society: Physical Sciences and Engineering Vol 349, 1689, pp 43-58 1994 It's available as compressed postscript via ftp or WWW in the directories ftp://ftp.cs.bham.ac.uk/pub/dist/cog_affect/ http://www.cs.bham.ac.uk/~axs/cog_affect in the file called Aaron.Sloman_semantics.ps.Z There's another paper extending some of the ideas, in the file Sloman.turing90.ps.Z (revised version of paper presented at the Turing90 colloquium, April 1990). Other papers in the same directory are all part of the same research programme, including work on motivation and emotions, and varieties of forms of representation. Aaron --- -- Aaron Sloman, ( http://www.cs.bham.ac.uk/~axs ) School of Computer Science, The University of Birmingham, B15 2TT, England EMAIL A.Sloman@cs.bham.ac.uk OR A.Sloman@bham.ac.uk Phone: +44-(0)121-414-4775 Fax: +44-(0)121-414-4281 ========================================================================== ====================================================================== From: PETER VAN ROY Conference: 1298 , +p.constraints To: ALL Message: 16 Reply To: 0 Subj: The Grand Challenge Date: 06/01/95 Time: 14:09 ---------------------------------------------------------------------- ÿ@FROM :vanroy@dfki.uni-sb.de N ÿ@ORIGIN :world N ÿ@UMSGID :<3qkhmj$e5s@hitchcock.dfki.uni-sb.de> N ÿ@UNEWSGR:01comp.lang.prolog,comp.lang.functional,comp.constraints,comN ÿ@UNEWSGR:02p.object.logic N From: vanroy@dfki.uni-sb.de (Peter Van Roy) Newsgroups: comp.lang.prolog,comp.lang.functional,comp.constraints,comp.object. logic Subject: The Grand Challenge Date: 1 Jun 1995 14:09:23 GMT Message-ID: <3qkhmj$e5s@hitchcock.dfki.uni-sb.de> Xref: uunet comp.lang.prolog:13070 comp.lang.functional:6045 comp.constraints:6 88 comp.object.logic:463 The Grand Challenge in Programming Languages -------------------------------------------- The Grand Challenge in programming languages is to build a *single* simple and practical system with *maximum* expressiveness. There is *no* system that provides such useful notions as concurrency, constraints, full compositionality , lexical scoping, search, typing, distribution and persistence, while remaining *simple*. Is this Grand Challenge ludicrous? Well, no. Major progress has been made. But there is still much to do. In logic programming, the concurrent constraint programming (CCP) community is tackling this problem head on and making amazing progress. We use the scientif ic method: isolate concepts one by one, reduce them to their essentials, and incorporate them. We exploit the power of formal models hand-in-hand with the experience of using practical systems. The CCP community is having major successes. For example: The AKL project at SICS was the first to integrate the problem-solving power of constraint logic programming into a concurrent and reactive language, thus solving a central outstanding problem of the Japanese Fifth Generation Project. Another example: The Oz project at the DFKI has first developed a fully-compositional generalization of CCP that gives first-class status to procedures, objects, and modules. The CCP community is world-wide and growing. The developers of the languages AKL (SICS, Sweden), Oz (DFKI, Germany) and LIFE (PRL, France and SFU, Canada) have collaborated closely over the last three years in the Esprit project ACCLAIM. The AKL and Oz projects are converging. LIFE technology is being integrated into Oz. CCP work is going on in many other places including Xerox PARC. The ToonTalk system, a successor to Logo, has CCP at its heart. The DFKI Oz system, released in January 1995, has struck a chord. An international Oz workshop WOz'95 is independently being organized in Switzerland. Various projects world-wide are using Oz as their main platform. The vision of Concurrent Constraint Programming is there and it is gaining momentum! Peter -- ------------------------------------------------------------------------- Peter Van Roy Programming Systems Lab Tel: +49-681-302-5332 DFKI Fax: +49-681-302-5341 Stuhlsatzenhausweg 3 Net: vanroy@dfki.uni-sb.de D-66123 Saarbruecken, Germany Web: http://ps-www.dfki.uni-sb.de/~vanroy ------------------------------------------------------------------------- Contact addresses for Oz are: oz@dfki.uni-sb.de Bug reports and questions oz-users@dfki.uni-sb.de To all Oz users oz-users-request@dfki.uni-sb.de Maintenance of the users list ------------------------------------------------------------------------- Vacation planning is a problem of mathematical logic. I want to go to A AND B AND C, but my budget only allows me to go to A OR B OR C. -- K. ------------------------------------------------------------------------- ============================================================================= fr====================================================================== From: MHB0 Conference: 1252 , comp.ai To: ALL Message: 258 Reply To: 0 Subj: New Book Announcement Date: 06/01/95 Time: 13:32 ---------------------------------------------------------------------- ÿ@FROM :mhb0@Lehigh.EDU N ÿ@UMSGID :<3qktir$1g0g@ns2-1.CC.Lehigh.EDU> N ÿ@UNEWSGR:01comp.ai N From: mhb0@Lehigh.EDU Newsgroups: comp.ai Subject: New Book Announcement Date: 1 Jun 1995 13:32:11 -0400 Message-ID: <3qktir$1g0g@ns2-1.CC.Lehigh.EDU> Xref: uunet comp.ai:30372 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. Mark H. Bickhard Department of Psychology 17 Memorial Drive East Lehigh University Bethlehem, PA 18015 610-758-3633