Consider the task under which I labour: These are supposed to be talks in the millennial spirit. My charge is to find, somewhere in the philosophical landscape, a problem of whose current status I can give some coherent account, and to point the direction in which it seems to me that further research might usefully proceed, And I'm to try to sound reasonably cheerful and optimistic in the course of doing so. No sooner did I begin to ponder these terms (...) of engagement, than it occurred to me that cheer and optimism aren't really my thing; also that I hadn't heard of a topic in the philosophy of mind which seems to me to be other than a godawful mess. It struck me that my best course would be for me to change my name and go into hiding. Thus my first choice of a title for this lecture, which was ‘To Be Announced’. (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)

This collection of 17 essays by the author offers a comprehensive theory of mind, encompassing traditional issues of consciousness and free will.

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

This introductory chapter attempts to clarify the philosophical, empirical, and theoretical bases on which a cognitive neuroscience approach to consciousness can be founded. We isolate three major empirical observations that any theory of consciousness should incorporate, namely (1) a considerable amount of processing is possible without consciousness, (2) attention is a prerequisite of consciousness, and (3) consciousness is required for some specific cognitive tasks, including those that require durable information maintenance, novel combinations of operations, or the spontaneous generation of intentional (...) behavior. We then propose a theoretical framework that synthesizes those facts: the hypothesis of a global neuronal workspace. This framework postulates that, at any given time, many modular cerebral networks are active in parallel and process information in an unconscious manner. An information becomes conscious, however, if the neural population that represents it is mobilized by top-down attentional amplification into a brain-scale state of coherent activity that involves many neurons distributed throughout the brain. The long-distance connectivity of these `workspace neurons' can, when they are active for a minimal duration, make the information available to a variety of processes including perceptual categorization, long-term memorization, evaluation, and intentional action. We postulate that this global availability of information through the workspace is what we subjectively experience as a conscious state. A complete theory of consciousness should explain why some cognitive and cerebral representations can be permanently or temporarily inaccessible to consciousness, what is the range of possible conscious contents, how they map onto specific cerebral circuits, and whether a generic neuronal mechanism underlies all of them. We confront the workspace model with those issues and identify novel experimental predictions. Neurophysiological, anatomical, and brain-imaging data strongly argue for a major role of prefrontal cortex, anterior cingulate, and the areas that connect to them, in creating the postulated brain-scale workspace. (shrink)

Is mental imagery pictorial? In Pylyshyn's view no empirical data provides convincing support to the “pictorial” hypothesis of mental imagery. Phenomenology, Pylyshyn says, is deeply deceiving and offers no explanation of why and how mental imagery occurs. We suggest that Pylyshyn mistakes phenomenology for what it never pretended to be. Phenomenological evidence, if properly considered, shows that mental imagery may indeed be pictorial, though not in the way that mimics visual perception. Moreover, Pylyshyn claims that the “pictorial hypothesis” is flawed (...) because the interpretation of “picture-like” objects in mental imagery takes a homunculus. However, the same point can be objected to Pylyshyn's own conclusion: if imagistic reasoning involves the same mechanisms and the same forms of representation as those that are involved in general reasoning, if they operate on symbol-based representations of the kind recommended by Pylyshyn (1984) and Fodor (1975), don't we need a phenomenological homunculus to tell an imagined bear from the real one? (shrink)

Simulation Theory says we need not rely exclusively on prepositional knowledge of other minds in order to explain the actions of others. Seeking to know what you will do, I imagine myself in your situation, and see what decision I come up with. I argue that this conception of simulation naturally generalizes: various bits of our mental machine can be run‘off‐line’, fulfilling functions other than those they were made for. In particular, I suggest that visual imagery results when the visual (...) system is run off‐line. I briefly review the empirical evidence and consider the philosophical implications, particularly concerning the mode of mental representation in imagery. (shrink)

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

To describe phenomena that occur at different time scales, computational models of the brain must incorporate different levels of abstraction. At time scales of approximately 1/3 of a second, orienting movements of the body play a crucial role in cognition and form a useful computational level embodiment level,” the constraints of the physical system determine the nature of cognitive operations. The key synergy is that at time scales of about 1/3 of a second, the natural sequentiality of body movements can (...) be matched to the natural computational economies of sequential decision systems through a system of implicit reference called deictic in which pointing movements are used to bind objects in the world to cognitive programs. This target article focuses on how deictic bindings make it possible to perform natural tasks. Deictic computation provides a mechanism for representing the essential features that link external sensory data with internal cognitive programs and motor actions. One of the central features of cognition, working memory, can be related to moment-by-moment dispositions of body features such as eye movements and hand movements. (shrink)

We argue that the presence of a word in an utterance serves as starting point for a relevance guided inferential process that results in the construction of a contextually appropriate sense. The linguistically encoded sense of a word does not serve as its default interpretation. The cases where the contextually appropriate sense happens to be identical to this linguistic sense have no particular theoretical significance. We explore some of the consequences of this view. One of these consequences is that there (...) may be many more mentally represented concepts than there are linguistically encoded concepts. (shrink)

In this book, Newell makes the case for unified theories by setting forth a candidate.

One effect of information technology is the increasing need to present information visually. The trend raises intriguing questions. What is the logical status of reasoning that employs visualization? What are the cognitive advantages and pitfalls of this reasoning? What kinds of tools can be developed to aid in the use of visual representation? This newest volume on the Studies in Logic and Computation series addresses the logical aspects of the visualization of information. The authors of these specially commissioned papers explore (...) the properties of diagrams, charts, and maps, and their use in problem solving and teaching basic reasoning skills. As computers make visual representations more commonplace, it is important for professionals, researchers and students in computer science, philosophy, and logic to develop an understanding of these tools; this book can clarify the relationship between visuals and information. (shrink)

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

Mathematicians at every level use diagrams to prove theorems. Mathematical Reasoning with Diagrams investigates the possibilities of mechanizing this sort of diagrammatic reasoning in a formal computer proof system, even offering a semi-automatic formal proof system—called Diamond—which allows users to prove arithmetical theorems using diagrams.

The chapters in this book have evolved from talks originally presented at The First International Workshop on Human and Machine Cognition.

A provocative assessment of human thought and behavior, reissued with a new afterword, explores a range of conundrums from the ability of the mind to perceive three dimensions to the nature of consciousness, in an account that draws on ...

Each of the chapters in this volume devotes considerable attention to defining and elaborating the notion of the frame problem-one of the hard problems of artificial intelligence. Not only do the chapters clarify the problems at hand, they shed light on the different approaches taken by those in artificial intelligence and by certain philosophers who have been concerned with related problems in their field. The book should therefore not be read merely as a discussion of the frame problem narrowly conceived, (...) but also as a general analysis of what could be a major challenge to the design of computer systems exhibiting general intelligence. (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)

Although the mechanics of how the eye works are well understood, debate still exists as to how the complex machinery of the brain interprets neural impulses...