The book from which these sections are excerpted is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as “mental organs.” These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated (...) structures along an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term.Various types of knowledge and modes of knowledge acquisition are discussed in these terms. Some of the properties of the language faculty are investigated. The basic cognitive relation is “knowing a grammar”; knowledge of language is derivative and, correspondingly, raises further problems. Language as commonly understood is not a unitary phenomenon but involves a number of interacting systems: the “computational” system of grammar, which provides the representations of sound and meaning that permit a rich range of expressive potential, is distinct from a conceptual system with its own properties; knowledge of language must be distinguished from knowledge of how to use a language; and the various systems that enter into the knowledge and use of language must be further analyzed into their specific subcomponents. (shrink)

Introduction: Something on the State of the Art 1 I. Functionalism and Realism 1. Operationalism and Ordinary Language 35 2. The Appeal to Tacit Knowledge in Psychological Explanations 63 3. What Psychological States are Not 79 4. Three Cheers for Propositional Attitudes 100 II. Reduction and Unity of Science 5. Special Sciences 127 6. Computation and Reduction 146 III. Intensionality and Mental Representation 7. Propositional Attitudes 177 8. Tom Swift and His Procedural Grandmother 204 9. Methodological Solipsism Considered as a (...) Research Strategy in Cognitive Psychology 225 IV. Nativism 10. The Present Status of the Innateness Controversy 257 Notes 317. (shrink)

Sydney Shoemaker notes that my "avoidance of the standard philosophical terminology for discussing such matters" often creates problems for me; philosophers have a hard time figuring out what I am saying and what I am denying. My refusal to play ball with my colleagues is deliberate, of course, since I view the standard philosophical terminology as worse than useless--a major obstacle to progress since it consists of so many errors trapped in the seductively lucid amber of tradition: "obvious truths" that (...) are simply false, broken-backed distinctions, and other cognitive illusions. I want to shift the perspective of philosophy of mind, and for that task using the standard terminology would be counterproductive. Fortunately, the inevitable communication-difficulties my policy provokes are forced into the open by occasions such as this constructive confrontation, permitting me to clarify my shocking message. I am grateful to Shoemaker, and to Michael Tye, Frank Jackson and David Rosenthal, for their vigorous and sympathetic reactions to my book. (shrink)

Connectionism and phenomenology can mutually inform and mutually constrain each other. In this manifesto I outline an approach to consciousness based on distinctions developed by connectionists. Two core identities are central to a connectionist theory of consciouness: conscious states of mind are identical to occurrent activation patterns of processing units; and the variable dispositional strengths on connections between units store latent and unconscious information. Within this broad framework, a connectionist model of consciousness succeeds according to the degree of correspondence between (...) the content of human consciousness (the world as it is experienced) and the interpreted content of the network. Constitutive self-awareness and reflective self-awareness can be captured in a model through its ability to respond to self-reflexive information, identify self-referential categories, and process information in the absence of simultaneous input. The qualitative feel of sensation appears in a model as states of activation that are not fully discriminated by later processing. Connectionism also uniquely explains several specific features of experience. The most important of these is the superposition of information in consciousness — our ability to perceive more than meets the eye, and to apprehend complex categorical and temporal information in a single highly-cognized glance. This superposition in experience matches a superposition of representational content in distributed representations. (shrink)

Accounting for phenomenal structure—the forms, aspects, and features of conscious experience—poses a deep challenge for the scientific study of consciousness, but rather than abandon hope I propose a way forward. Connectionism, I argue, offers a bi-directional analogy, with its oft-noted “neural inspiration” on the one hand, and its largely unnoticed capacity to illuminate our phenomenology on the other. Specifically, distributed representations in a recurrent network enable networks to superpose categorical, contextual, and temporal information on a specific input representation, much as (...) our own experience does. Artificial neural networks also suggest analogues of four salient distinctions between sensory and nonsensoty consciousness. The paper concludes with speculative proposals for discharging the connectionist heuristics to leave a robust, detailed empirical theory of consciousness. (shrink)

In this richly detailed analysis, Barbara Von Eckardt lays the foundations for understanding what it means to be a cognitive scientist.

The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

On the occasion of a first conference on Cognitive Science, it seems appropriate to review the basis of common understanding between the various disciplines. In my estimate, the most fundamental contribution so far of artificial intelligence and computer science to the joint enterprise of cognitive science has been the notion of a physical symbol system, i.e., the concept of a broad class of systems capable of having and manipulating symbols, yet realizable in the physical universe. The notion of symbol so (...) defined is internal to this concept, so it becomes a hypothesis that this notion of symbols includes the symbols that we humans use every day of our lives. In this paper we attempt systematically, but plainly, to lay out the nature of physical symbol systems. Such a review is in ways familiar, but not thereby useless. Restatement of fundamentals is an important exercise. (shrink)

Michael Tye untangles the complex web of empirical and conceptual issues of the newly revived imagery debate in psychology between those that liken mental...

The book also introduces a host of new experimental techniques and major hypotheses to guide future research.

Preface 1 Introduction: The Persistence of the Attitudes 2 Individualism and Supervenience 3 Meaning Holism 4 Meaning and the World Order Epilogue Creation Myth Appendix Why There Still Has to be a Language of Thought Notes References Author Index.

This book is not a conventional introduction to the philosophy of mind, nor is it a contribution to the physicalist/ dualist debate. Instead The Representational Theory of Mind demonstrates that we can construct physicalist theories of important aspects of our mental life. Its aim is to explain and defend a physicalist theory of intelligence in two parts: the first six chapters consist of an exposition, elaboration and defence of human sentience (the functionalist theory of mind), and the second part considers (...) rivals and objections to this theory. Kim Sterelny aims to introduce people to this area of philosophy by exemplifying it, to show that philosophical and empirical investigations can be synthesized to the benefit of both. --From publisher's description. (shrink)

The book from which these sections are excerpted is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated structures along (...) an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term. (shrink)

Thoughts and other mental states are defined by their role in a functional system. Since it is easier to determine when we have knowledge than when reasoning has occurred, Gilbert Harman attempts to answer the latter question by seeing what assumptions about reasoning would best account for when we have knowledge and when not. He describes induction as inference to the best explanation, or more precisely as a modification of beliefs that seeks to minimize change and maximize explanatory coherence. Originally (...) published in 1973. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905. (shrink)

Consciousness is a mongrel concept: there are a number of very different "consciousnesses." Phenomenal consciousness is experience; the phenomenally conscious aspect of a state is what it is like to be in that state. The mark of access-consciousness, by contrast, is availability for use in reasoning and rationally guiding speech and action. These concepts are often partly or totally conflated, with bad results. This target article uses as an example a form of reasoning about a function of "consciousness" based on (...) the phenomenon of blindsight. Some information about stimuli in the blind field is represented in the brains of blindsight patients, as shown by their correct "guesses," but they cannot harness this information in the service of action, and this is said to show that a function of phenomenal consciousness is somehow to enable information represented in the brain to guide action. But stimuli in the blind field are BOTH access-unconscious and phenomenally unconscious. The fallacy is: an obvious function of the machinery of access-consciousness is illicitly transferred to phenomenal consciousness. (shrink)

Little, Brown, 1992 Review by Glenn Branch on Jul 5th 1999 Volume: 3, Number: 27.

Cognitive Science is a single-source undergraduate text that broadly surveys the theories and empirical results of cognitive science within a consistent computational perspective. In addition to covering the individual contributions of psychology, philosophy, linguistics, and artificial intelligence to cognitive science, the book has been revised to introduce the connectionist approach as well as the classical symbolic approach and adds a new chapter on cognitively related advances in neuroscience. Cognitive science is a rapidly evolving field that is characterized by considerable contention (...) among different views and approaches. Cognitive Science presents these in a relatively neutral manner. It covers many new orientations theories and findings, embedding them in an integrated computational perspective and establishing a sense of continuity and contrast with more traditional work in cognitive science. The text assumes no prerequisite knowledge, introducing all topics in a uniform, accessible style. Many topics, such as natural language processing and vision, however, are developed in considerable depth, which allows the book to be used with more advanced undergraduates or even in beginning graduate settings. A Bradford Book. (shrink)

The philosophy of cognitive science has recently become one of the most exciting and fastest growing domains of philosophical inquiry and analysis. Until the early 1980s, nearly all of the models developed treated cognitive processes -- like problem solving, language comprehension, memory, and higher visual processing -- as rule-governed symbol manipulation. However, this situation has changed dramatically over the last half dozen years. In that period there has been an enormous shift of attention toward connectionist models of cognition that are (...) inspired by the network-like architecture of the brain. Because of their unique architecture and style of processing, connectionist systems are generally regarded as radically different from the more traditional symbol manipulation models. This collection was designed to provide philosophers who have been working in the area of cognitive science with a forum for expressing their views on these recent developments. Because the symbol-manipulating paradigm has been so important to the work of contemporary philosophers, many have watched the emergence of connectionism with considerable interest. The contributors take very different stands toward connectionism, but all agree that the potential exists for a radical shift in the way many philosophers think of various aspects of cognition. Exploring this potential and other philosophical dimensions of connectionist research is the aim of this volume. (shrink)

For the uninitiated, there are two major tendencies in the modeling of human cognition. The older, tradtional school believes, in essence, that full human cognition can be modeled by dividing the world up into distinct entities -- called __symbol s__-- such as “dog”, “cat”, “run”, “bite”, “happy”, “tumbleweed”, and so on, and then manipulating this vast set of symbols by a very complex and very subtle set of rules. The opposing school claims that this system, while it might be good (...) at concluding that Paris is the capital of France or that there must be blood flowing in the left-rear leg of a cow, can never capture the full measure -- indeed, the essence -- of human cognition. For them, the essential features of cognition emerge from the combined effects of myriad, tiny actions far below the surface of consciousness. This is the camp to which Paul Churchland belongs. (shrink)

The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach is that there is a natural domain of (...) human functioning that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis. Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the " cognitive impenetrability condition." Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the "degrees of freedom" problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories. (shrink)

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality (...) of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of? (shrink)

The character of computational modelling of cognition depends on an underlying theory of representation. Classical cognitive science has exploited the syntax/semantics theory of representation that derives from logic. But this has had the consequence that the kind of psychological explanation supported by classical cognitive science is " _conceptualist_: " psychological phenomena are modelled in terms of relations that hold between concepts, and between the sensors/effectors and concepts. This kind of explanation is inappropriate for the Proper Treatment of Connectionism.

Evidence and theory ranging from traditional philosophy to contemporary cognitive research support the hypothesis that consciousness has a two-part structure: a focused region of articulated experience surrounded by a field of relatively unarticulated, vague experience.William James developed an especially useful phenomenological analysis of this "fringe" of consciousness, but its relation to, and potential value for, the study of cognition has not been explored. I propose strengthening James′ work on the fringe with a functional analysis: fringe experiences work to radically condense (...) context information in consciousness; are vague because a more explicit representation of context information would overwhelm consciousness′ limited articulation capacity; help mediate retrieval functions in consciousness; and contain a subset of monitoring and control experiences that cannot be elaborated in focal attention and are "ineffable." In general, the phenomenology of the fringe is a consequence of its cognitive functions, constrained by consciousness′ limited articulation capacity. Crucial to monitoring and control is the feeling of "rightness." Rightness functions as a summary index of cognitive integration, representing, in the fringe, the degree of positive fit between a given conscious content and its parallel, unconsciously encoded context. Rightness appears analogous to the connectionist metric of global network integration, known variously as goodness-of-fit, harmony, or minimum energy. (shrink)