FOUNDATIONAL ISSUES IN ARTIFICIAL INTELLIGENCE AND COGNITIVE SCIENCE IMPASSE AND SOLUTION Mark H. Bickhard Lehigh University Loren Terveen AT&T Bell Laboratories forthcoming, 1995 Elsevier Science Publishers 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 vi 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 vii 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 viii 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 ENCODINGS 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 ix 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 xii Preface 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. The book has gestated and grown over several years. Thanks are due to many people who have contributed to its development, with multitudinous comments, criticisms, discussions, and suggestions on both the manuscript and the ideas behind it. These include, Gordon Bearn, Lesley Bickhard, Don Campbell, Robert Campbell, Bill Clancey, Bob Cooper, Eric Dietrich, Carol Feldman, Ken Ford, Charles Guignon, Cliff Hooker, Norm Melchert, Benny Shanon, Peter Slezak, and Tim Smithers. Deepest thanks are also due to the Henry R. Luce Foundation for support to Mark Bickhard during the final years of this project. Mark H. Bickhard Henry R. Luce Professor of Cognitive Robotics & the Philosophy of Knowledge Department of Psychology 17 Memorial Drive East Lehigh University Bethlehem, PA 18015 [email protected]