What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

The renowned philosopher Jerry Fodor, a leading figure in the study of the mind for more than twenty years, presents a strikingly original theory on the basic constituents of thought. He suggests that the heart of cognitive science is its theory of concepts, and that cognitive scientists have gone badly wrong in many areas because their assumptions about concepts have been mistaken. Fodor argues compellingly for an atomistic theory of concepts, deals out witty and pugnacious demolitions of rival theories, and (...) suggests that future work on human cognition should build upon new foundations. This lively, conversational, and superbly accessible book is the first volume in the Oxford Cognitive Science Series, where the best original work in this field will be presented to a broad readership. Concepts will fascinate anyone interested in contemporary work on mind and language. Cognitive science will never be the same again. (shrink)

How the Body Shapes the Mind is an interdisciplinary work that addresses philosophical questions by appealing to evidence found in experimental psychology, neuroscience, studies of pathologies, and developmental psychology. There is a growing consensus across these disciplines that the contribution of embodiment to cognition is inescapable. Because this insight has been developed across a variety of disciplines, however, there is still a need to develop a common vocabulary that is capable of integrating discussions of brain mechanisms in neuroscience, behavioural expressions (...) in psychology, design concerns in artificial intelligence and robotics, and debates about embodied experience in the phenomenology and philosophy of mind. Shaun Gallagher's book aims to contribute to the formulation of that common vocabulary and to develop a conceptual framework that will avoid both the overly reductionistic approaches that explain everything in terms of bottom-up neuronal mechanisms, and inflationistic approaches that explain everything in terms of Cartesian, top-down cognitive states. Gallagher pursues two basic sets of questions. The first set consists of questions about the phenomenal aspects of the structure of experience, and specifically the relatively regular and constant features that we find in the content of our experience. If throughout conscious experience there is a constant reference to one's own body, even if this is a recessive or marginal awareness, then that reference constitutes a structural feature of the phenomenal field of consciousness, part of a framework that is likely to determine or influence all other aspects of experience. The second set of questions concerns aspects of the structure of experience that are more hidden, those that may be more difficult to get at because they happen before we know it. They do not normally enter into the content of experience in an explicit way, and are often inaccessible to reflective consciousness. To what extent, and in what ways, are consciousness and cognitive processes, which include experiences related to perception, memory, imagination, belief, judgement, and so forth, shaped or structured by the fact that they are embodied in this way? (shrink)

In Natural-Born Cyborgs, Clark argues that what makes humans so different from other species is our capacity to fully incorporate tools and supporting cultural ...

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

A Critique of Artificial Reason Hubert L. Dreyfus . HUBERT L. DREYFUS What Computers Still Can't Do Thi s One XZKQ-GSY-8KDG What. WHAT COMPUTERS STILL CAN'T DO Front Cover.

In _Reconstructing the Cognitive World_, Michael Wheeler argues that we should turn away from the generically Cartesian philosophical foundations of much contemporary cognitive science research and proposes instead a Heideggerian approach. Wheeler begins with an interpretation of Descartes. He defines Cartesian psychology as a conceptual framework of explanatory principles and shows how each of these principles is part of the deep assumptions of orthodox cognitive science. Wheeler then turns to Heidegger's radically non-Cartesian account of everyday cognition, which, he argues, can (...) be used to articulate the philosophical foundations of a genuinely non-Cartesian cognitive science. Finding that Heidegger's critique of Cartesian thinking falls short, even when supported by Hubert Dreyfus's influential critique of orthodox artificial intelligence, Wheeler suggests a new Heideggerian approach. He points to recent research in "embodied-embedded" cognitive science and proposes a Heideggerian framework to identify, amplify, and clarify the underlying philosophical foundations of this new work. He focuses much of his investigation on recent work in artificial intelligence-oriented robotics, discussing, among other topics, the nature and status of representational explanation, and whether cognition is computation rather than a noncomputational phenomenon best described in the language of dynamical systems theory. Wheeler's argument draws on analytic philosophy, continental philosophy, and empirical work to "reconstruct" the philosophical foundations of cognitive science in a time of a fundamental shift away from a generically Cartesian approach. His analysis demonstrates that Heideggerian continental philosophy and naturalistic cognitive science need not be mutually exclusive and shows further that a Heideggerian framework can act as the "conceptual glue" for new work in cognitive science. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

Ruth Millikan is well known for having developed a strikingly original way for philosophers to seek understanding of mind and language, which she sees as biological phenomena. She now draws together a series of groundbreaking essays which set out her approach to language. Guiding the work of most linguists and philosophers of language today is the assumption that language is governed by prescriptive normative rules. Millikan offers a fundamentally different way of viewing the partial regularities that language displays, comparing them (...) to biological norms that emerge from natural selection. This yields novel and quite radical consequences for our understanding of the nature of public linguistic meaning, the process of language understanding, how children learn language, and the semantics/pragmatics distinction. (shrink)

In the final essay, the "intrinsic" nature of "qualia" is compared with the naively imagined "intrinsic value" of a dollar in ...

What place does consciousness have in the natural world? If we reject materialism, could there be a credible alternative? In one classic example, philosophers ask whether we can ever know what is it is like for bats to sense the world using sonar. It seems obvious to many that any amount of information about a bat's physical structure and information processing leaves us guessing about the central questions concerning the character of its experience. A Place for Consciousness begins with reflections (...) on the existence of this gap. Is it just a psychological shortcoming in our merely human understanding of the physical world? Is it a trivial consequence of the simple fact that we just cannot be bats? Or does it mean there really are facts about consciousness over and above the physical facts? If so, what does consciousness do? Why does it exist? Rosenberg sorts out these problems, especially those centering on the causal role of consciousness. He introduces a new paradigm called Liberal Naturalism for thinking about what causation is, about the natural world, and about how to create a detailed model to go along with the new paradigm. Arguing that experience is part of the categorical foundations of causality, he shows that within this new paradigm there is a place for something essentially like consciousness in all its traditional mysterious respects. A striking feature of Liberal Naturalism is that its central tenets are motivated independently of the mind-body problem, by analyzing causation itself. Because of this approach, when consciousness shows up in the picture it is not introduced in an ad hoc way, and its most puzzling features can be explained from first principles. Ultimately, Rosenberg's final solution gives consciousness a causally important role without supposing either that it is physical or that it interacts with the physical. (shrink)

This edition has been fully revised and updated, and includes a new chapter on consciousness and a new section on modularity. There are also guides for further reading, and a new glossary of terms such as mentalese, connectionism, and the homunculus fallacy.

By definition zombies would be physically and behaviourally just like us, but not conscious. This currently very influential idea is a threat to all forms of physicalism, and has led some philosophers to give up physicalism and become dualists. It has also beguiled many physicalists, who feel forced to defend increasingly convoluted explanations of why the conceivability of zombies is compatible with their impossibility. Robert Kirk argues that the zombie idea depends on an incoherent view of the nature of phenomenal (...) consciousness. His book has two main aims. One is to demolish the zombie idea once and for all. There are plenty of objections to it in the literature, but they lack intuitive appeal. He offers a striking new argument which reveals fundamental confusions in the implied conception of consciousness. The book's other main contribution is to develop a fresh and original approach to the true nature of phenomenal consciousness. Kirk argues that a necessary condition is a 'basic package' of capacities. An important component of his argument is that the necessary cognitive capacities are not as sophisticated as is often assumed. By focusing on humbler creatures than ourselves he avoids some of the distracting complications of our sophisticated forms of cognition. The basic package does not seem to be sufficient for phenomenal consciousness. What is also needed is 'direct activity' - a special feature of the way the events which constitute incoming perceptual information affect the system. This is an integrated process, to be conceived of holistically, and contrasts sharply with what is often called the 'availability' or 'poisedness' of perceptual information. This original, penetrating, and readable book will be of interest to all who have a serious concern with the nature of consciousness: not only professional philosophers and students, but psychologists and neuroscientists. (shrink)

What is the relation between the material, conventional symbol structures that we encounter in the spoken and written word, and human thought? A common assumption, that structures a wide variety of otherwise competing views, is that the way in which these material, conventional symbol-structures do their work is by being translated into some kind of content-matching inner code. One alternative to this view is the tempting but thoroughly elusive idea that we somehow think in some natural language (such as English). (...) In the present treatment I explore a third option, which I shall call the "complementarity" view of language. According to this third view the actual symbol structures of a given language add cognitive value by complementing (without being replicated by) the more basic modes of operation and representation endemic to the biological brain. The "cognitive bonus" that language brings is, on this model, not to be cashed out either via the ultimately mysterious notion of "thinking in a given natural language" or via some process of exhaustive translation into another inner code. Instead, we should try to think in terms of a kind of coordination dynamics in which the forms and structures of a language qua material symbol system play a key and irreducible role. Understanding language as a complementary cognitive resource is, I argue, an important part of the much larger project (sometimes glossed in terms of the "extended mind") of understanding human cognition as essentially and multiply hybrid: as involving a complex interplay between internal biological resources and external non-biological resources. (shrink)

Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence. According to an article in The New York Times, the course on artificial intelligence is (...) “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson author Dr. Jennifer Widom. Artificial Intelligence: A Modern Approach, 3e is available to purchase as an eText for your Kindle™, NOOK™, and the iPhone®/iPad®. (shrink)

This article focuses on the problem of representational content. Accounting for representational content is the central issue in contemporary naturalism: it is the major remaining task facing a naturalistic conception of the world. Representational content is also the central barrier to contemporary cognitive science and artificial intelligence: it is not possible to understand representation in animals nor to construct machines with genuine representation given current (lack of) understanding of what representation is. An elaborated critique is offered to current approaches to (...) representation, arguing that the basic underlying approach is, at root, logically incoherent, and, thus, that standard approaches are doomed to failure. An alternative model of representation - interactivism - is presented that avoids or solves the problems facing standard approaches. Interactivism is framed by a version of functionalism, and a naturalization of that functionalism completes an outline of a naturalization of representation and representational content. (shrink)

This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and (...) hence that none of them provides a valid solution to the SGP, which remains an open problem. (shrink)

This paper applies a teleosemantic perspective to the question of whether there is genuine representation outside the familiar realm of belief‐desire psychology. I first explain how teleosemantics accounts for the representational powers of beliefs and desires themselves. I then ask whether biological states which are simpler than beliefs and desires can also have representational powers. My conclusion is that such biologically simple states can be ascribed representational contents, but only in a system‐relative way: such states must be ascribed varying contents (...) when viewed as components in different biological systems. I conclude by arguing that ‘the genetic code’ does not even embody this kind of system‐relative representation. (shrink)

We all believe an unbounded number of things about the way the world is and about the way the world works. For example, I believe that if I move this book into the other room, it will not change color -- unless there is a paint shower on the way, unless I carry an umbrella through that shower, and so on; I believe that large red trucks at high speeds can hurt me, that trucks with polka dots can hurt me, (...) and so on; that if I move this book, the room will stay in place -- unless there is a pressure switch under the book attached to a bomb, unless the switch communicates to the bomb by radio and there is shielding in the way, and so on; that the moon is not made of green cheese, that the moon is not made of caviar, that the moon is not made of gold, and so on. The problems involved in accounting for such infinite proliferations of beliefs -- and the computations and inferences that take them into account -- are collectively called the Frame Problems, and are considered by some to constitute a major discovery of a new philosophical problem. How could we possibly learn them all? How could the brain possibly hold them all? The problems appear insoluble, impossible. Yet we all learn and hold such unbounded numbers of beliefs; in particular, children do. Something must be wrong. I wish to argue that the frame problem arises from a fundamental presupposition about the nature of representation -- a false presupposition. Yet, it is a presupposition that dominates contemporary developmental psychology (and psychology more broadly, and cognitive science, artificial intelligence, philosophy of mind, and so on). In particular, I will offer an alternative model of the nature of representation within which the frame problem does not arise -- within which such unboundedness is natural. (shrink)

In his recent papers, entitled Intelligence without Representation and Intelligence without Reason, Brooks argues for mobile robots as the foundation of AI research. This article argues that even if we seek to investigate complete agents in real-world environments, robotics is neither necessary nor sufficient as a basis for AI research. The article proposes real-world software environments, such as operating systems or databases, as a complementary substrate for intelligent-agent research and considers the relative advantages of software environments as test beds for (...) AI. First, the cost, effort, and expertise necessary to develop and systematically experiment with software artifacts are relatively low. Second, software environments circumvent many thorny but peripheral research issues that are inescapable in physical environments. Brooks's mobile robots tug AI toward a bottom-up focus in which the mechanics of perception and mobility mingle inextricably with or even supersede core AI research. In contrast, the softbots (software robots) I advocate facilitate the study of classical AI problems in real-world (albeit, software) domains. For example, the UNIX softbot under development at the University of Washington has led us to investigate planning with incomplete information, interleaving planning and execution, and a host of related high-level issues. (shrink)

A mechanism for planning ahead would appear to be essential to any creature with more than insect level intelligence. In this paper it is shown how planning, using full means-ends analysis, can be had while avoiding the so called symbol grounding problem. The key role of knowledge representation in intelligence has been acknowledged since at least the enlightenment, but the advent of the computer has made it possible to explore the limits of alternate schemes, and to explore the nature of (...) our everyday understanding of the world around us. In particular, artificial intelligence (AI) and robotics has forced a close examination, by people other than philosophers, of what it means to say for instance that "snow is white." One interpretation of the "new AI" is that it is questioning the need for representation altogether. Brooks and others have shown how a range of intelligent behaviors can be had without representation, and this paper goes one step further showing how intending to do things can be achieved without symbolic representation. The paper gives a concrete example of a mechanism in terms of robots that play soccer. It describes a belief, desire and intention (BDI) architecture that plans in terms of activities. The result is a situated agent that plans to do things with no more ontological commitment than the reactive systems Brooks described in his seminal paper, "Intelligence without Representation.". (shrink)