b>. Recent findings in cognitive science suggest that the epistemic subject is more complex and epistemically porous than is generally pictured. Human knowers are open to the world via multiple channels, each operating for particular purposes and according to its own logic. These findings need to be understood and addressed by the philosophical community. The current essay argues that one consequence of the new findings is to invalidate certain arguments for epistemic anti-realism.

1. The Naturalistic Turn in Philosophy of Science 2. The Framework of Mechanistic Explanation: Parts, Operations, and Organization 3. Representing and Reasoning About Mechanisms 4. Mental Mechanisms: Mechanisms that Process Information 5. Discovering Mental Mechanisms 6 . Summary.

Given the controversial nature of most issues in the foundations of cognitive science, it could hardly be expected from a description of the territory that ...

Some of Kant's ideas about the mind have had a huge influence on cognitive science, in particular his view that sensory input has to be worked up using concepts or concept-like states and his conception of the mind as a system of cognitive functions. We explore these influences in the first part of the paper. Other ideas of Kant's about the mind have not been assimilated into cognitive science, including important ideas about processes of synthesis, mental unity, and consciousness and (...) self-consciousness. They are the topic of the second part of the paper. (shrink)

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...) recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (shrink)

In order to investigate cognition fundamental assumptions must be made about what, in general terms, it is. In cognitive science it is usually assumed that cognition is computational and representational. There have been well known disputes over these assumptions, with rival claims that cognition is dynamical, situated and embodied. In this paper I emphasize the relations between cognition and control. I present a model of cognition that makes the claim that it is a form of high-order control, and I argue (...) that viewing cognition as high-order control could be a useful framework assumption for cognitive science. Cognition has many aspects and different concepts can emphasize different aspects of it. Computational and representational assumptions have been very productive, and dynamical and embodied assumptions have also been productive, though to a much lesser extent so far. Control, however, has received insufficient attention in cognition science. The model I propose is based on a point that few will dispute, namely that control of behavior is the ultimate function of cognition. Bringing this to the foreground can be productive by highlighting the ways in which cognition is structured in relation to this control function. If this perspective is valuable it will be because the control function has a highly structuring effect on cognition. As a result a control-based perspective will predict many features of cognition and yield a coherent, integrated picture. (shrink)

Standard approaches to cognition emphasise structures (representations and rules) much more than processes, in part because this appears to be necessary to capture the normative features of cognition. However the resultant models are in?exible and face the problem of computational intractability. I argue that the ability of real world cognition to cope with complexity results from deep and subtle coupling between cognitive and non-cognitive processes. In order to capture this, theories of cognition must shift from a structural rule-de?ned conception of (...) cognition to a thoroughgoing embedded process approach. (shrink)

Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate (...) that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility. (shrink)

Expanded version of a chapter to appear in The Oxford Handbook of Contemporary Analytic Philosophy, edited by Frank Jackson and Michael Smith (Oxford: Oxford University Press, 2005).

The so-called ‘cognitive revolution’ (Gardner, 1985) in American psychology owed much to developments in adjacent disciplines, especially theoretical linguistics and computer science. Indeed, the cognitive revolution brought forth, not only a change in the conception of psychology, but also an inter-disciplinary approach to understanding the mind, involving philosophy, anthropology and neuroscience along with computer science, linguistics and psychology. Many commentators agree in dating the conception of this inter-disciplinary approach, cognitive science, to 11 September 1956, the second day of a symposium (...) on information theory held at MIT (Miller, 2003). Over the next twenty years or so, cognitive science developed an institutional presence through research centres, conferences, journals, and a substantial infusion of funds from the Alfred P. Sloan Foundation. (shrink)

Is an individual agent constitutive of or constituted by its social interactions? This question is typically not asked in the cognitive sciences, so strong is the consensus that only individual agents have constitutive efficacy. In this article we challenge this methodological solipsism and argue that interindividual relations and social context do not simply arise from the behavior of individual agents, but themselves enable and shape the individual agents on which they depend. For this, we define the notion of autonomy as (...) both a characteristic of individual agents and of social interaction processes. We then propose a number of ways in which interactional autonomy can influence individuals. Then we discuss recent work in modeling on the one hand and psychological investigations on the other that support and illustrate this claim. Finally, we discuss some implications for research on social and individual agency. (shrink)

Clearly the Cartesian ontological commitments that have dominated the scientific study of the mind up to the present have not been helpful. ...

This article provides a retrospective, current and prospective overview on developments in brain research and neuroscience. Both theoretical and empirical studies are considered, with emphasis in the concept of multivariability and metastability in the brain. In this new view on the human brain, the potential multivariability of the neuronal networks appears to be far from continuous in time, but confined by the dynamics of short-term local and global metastable brain states. The article closes by suggesting some of the implications of (...) this view in future multidisciplinary brain research. (shrink)

Consciousness emerges as the key topic in this second edition of Owen Flanagan's popular introduction to cognitive science and the philosophy of psychology....

This collection of readings shows how cognitive science can influence most of the primary branches of philosophy, as well as how philosophy critically examines...

The `developmental systems'' perspective in biology is intended to replace the idea of a genetic program. This new perspective is strongly convergent with recent work in psychology on situated/embodied cognition and on the role of external `scaffolding'' in cognitive development. Cognitive processes, including those which can be explained in evolutionary terms, are not `inherited'' or produced in accordance with an inherited program. Instead, they are constructed in each generation through the interaction of a range of developmental resources. The attractors which (...) emerge during development and explain robust and/or widespread outcomes are themselves constructed during the process. At no stage is there an explanatory stopping point where some resources control or program the rest of the developmental cascade. `Human nature'' is a description of how things generally turn out, not an explanation of why they turn out that way. Finally, we suggest that what is distinctive about human development is its degree of reliance on external scaffolding. (shrink)

Philosophy interfaces with cognitive science in three distinct but related areas. First, there is the usual set of issues that fall under the heading of philosophy of science (explanation, reduction, etc.), applied to the special case of cognitive science. Second, there is the endeavor of taking results from cognitive science as bearing upon traditional philosophical questions about the mind, such as the nature of mental representation, consciousness, free will, perception, emotions, memory, etc. Third.

What is required to be an interdisciplinary theory in cognitive science is for it to span more than one traditional domain. Generally speaking, as I discuss ...

2. Invariant Sensorimotor Features ("Affordances"). To say this is not to declare oneself a Gibsonian, whatever that means. It is merely to point out that what a sensorimotor system can do is determined by what can be extracted from its motor interactions with its sensory input. If you lack sonar sensors, then your sensorimotor system cannot do what a bat's can do, at least not without the help of instruments. Light stimulation affords color vision for those of us with the (...) right sensory apparatus, but not for those of us who are color-blind. The geometric fact that, when we move, the "shadows" cast on our retina by nearby objects move faster than the shadows of further objects means that, for those of us with normal vision, our visual input affords depth perception. From more complicated facts of projective and solid geometry it follows that a 3-dimensional shape, such as, say, a boomerang, can be recognized as being the same shape Ð and the same size Ð even though the size and shape of its shadow on our retinas changes as we move in relation to it or it moves in relation to us. Its shape is said to be invariant under these sensorimotor transformations, and our visual systems can detect and extract that invariance, and translate it into a visual constancy. So we keep seeing a boomerang of the same shape and size even though the shape and size of its retinal shadows keep changing. (shrink)

Behavioral scientists studied behavior; cognitive scientists study what generates behavior. Cognitive science is hence theoretical behaviorism (or behaviorism is experimental cognitivism). Behavior is data for a cognitive theorist. What counts as a theory of behavior? In this paper, a methodological constraint on theory construction -- "neoconstructivism" -- will be proposed (by analogy with constructivism in mathematics): Cognitive theory must be computable; given an encoding of the input to a behaving system, a theory must be able to compute (an encoding of) (...) its outputs. It is a mistake to conclude, however, that this constraint requires cognitive theory to be computational, or that it follows from this that cognition is computation. (shrink)

Since 1969, when Dennett introduced a distinction between personal and sub-personal levels of explanation, many philosophers have used 'sub-personal' very loosely, and Dennett himself has abandoned a view of the personal level as genuinely autonomous. I recommend a position in which Dennett's original distinction is crucial, by arguing that the phenomenon called mental causation is on view only at the properly personal level. If one retains the commit-' ments incurred by Dennett's early distinction, then one has a satisfactory anti-physicalistic, anti-dualist (...) philosophy of mind. It neither interferes with the projects of sub-personal psychology, nor encourages ; instrumentalism at the personal level. (shrink)

Drawing on philosophy, neuroscience, and artificial intelligence, Simple Minds explores the construction of the mind from the matter of the brain.

Pickering and Chater (P&C) maintain that folk psychology and cognitive science should neither compete nor cooperate. Each is an independent enterprise, with a distinct subject matter and characteristic modes of explanation. P&C''s case depends upon their characterizations of cognitive science and folk psychology. We question the basis for their characterizations, challenge both the coherence and the individual adequacy of their contrasts between the two, and show that they waver in their views about the scope of each. We conclude that P&C (...) do not so muchdiscover ascreate the gap they find between folk psychology and cognitive science. It is an artifact of their implausible and unmotivated attempt to demarcate the two areas, and of the excessively narrow accounts they give of each. (shrink)

It is often assumed that cognitive science is built upon folk psychology, and that challenges to folk psychology are therefore challenges to cognitive science itself. We argue that, in practice, cognitive science and folk psychology treat entirely non-overlapping domains: cognitive science considers aspects of mental life which do not depend on general knowledge, whereas folk psychology considers aspects of mental life which do depend on general knowledge. We back up our argument on theoretical grounds, and also illustrate the separation between (...) cognitive scientific and folk psychological phenomena in a number of cognitive domains. We consider the methodological and theoretical significance of our arguments for cognitive science research. (shrink)

In my book How the Mind Works, I defended the theory that the human mind is a naturally selected system of organs of computation. Jerry Fodor claims that 'the mind doesn't work that way'(in a book with that title) because (1) Turing Machines cannot duplicate humans' ability to perform abduction (inference to the best explanation); (2) though a massively modular system could succeed at abduction, such a system is implausible on other grounds; and (3) evolution adds nothing to our understanding (...) of the mind. In this review I show that these arguments are flawed. First, my claim that the mind is a computational system is different from the claim Fodor attacks (that the mind has the architecture of a Turing Machine); therefore the practical limitations of Turing Machines are irrelevant. Second, Fodor identifies abduction with the cumulative accomplishments of the scientific community over millennia. This is very different from the accomplishments of human common sense, so the supposed gap between human cognition and computational models may be illusory. Third, my claim about biological specialization, as seen in organ systems, is distinct from Fodor's own notion of encapsulated modules, so the limitations of the latter are irrelevant. Fourth, Fodor's arguments dismissing of the relevance of evolution to psychology are unsound. (shrink)

This is indeed an auspicious time for Cognitive Science. I stand here before you this evening as the first Chair to give a presidential address to this austere body, to place on record before you what you are to accept as the Society's official view on the new science of the mind.

Neuroscientists have an advantage on us dry Cognitive Scientists: They always have impressive color slides of PET or fMRI images showing the exact location of whatever they wish to discuss --” the soul or the locus of sinful thoughts or the center of consciousness. If one were to go by popular science articles on the brain one would have to conclude that we know where everything is located in the brain and therefore we know everything about it except how it (...) manages to do things like think. Yet I believe that what we do here at the Center for Cognitive Science is precisely that we study what is in the mind, even if we do not know where it is in the brain (and in fact even if there is no answer to the question where it is in the brain --“ which is indeed the case for any interesting mental mechanism or mental state). Let me explain. (shrink)

Our response amplifies our case for scientific realism and the unity of science and clarifies our commitments to scientific unity, nonreductionism, behaviorism, and our rejection of talk of “emergence.” We acknowledge support from commentators for our view of physics and, responding to pressure and suggestions from commentators, deny the generality supervenience and explain what this involves. We close by reflecting on the relationship between philosophy and science.

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...) recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (shrink)

This is a revised version of the introductory essay in C. Eschenbach, C. Habel and B. Smith (eds.), Topological Foundations of Cognitive Science, Hamburg: Graduiertenkolleg Kognitionswissenschaft, 1994, the text of a talk delivered at the First International Summer Institute in Cognitive Science in Buffalo in July 1994.

This volume introduces central issues in cognitive science by means of debates on key questions.

This article addresses issues in developing cognitive architectures--generic computational models of cognition. Cognitive architectures are believed to be essential in advancing understanding of the mind, and therefore, developing cognitive architectures is an extremely important enterprise in cognitive science. The article proposes a set of essential desiderata for developing cognitive architectures. It then moves on to discuss in detail some of these desiderata and their associated concepts and ideas relevant to developing better cognitive architectures. It argues for the importance of taking (...) into full consideration these desiderata in developing future architectures that are more cognitively and ecologically realistic. A brief and preliminary evaluation of existing cognitive architectures is attempted on the basis of these ideas. (shrink)

The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among entities at a high (...) level can be reduced to causal relationships among simpler entities at a more detailed level. We argue that a similar hierarchy makes possible an equally productive approach toward cognitive modeling. The levels of models that we conceive in relation to cognition include, at the highest level, sociological/anthropological models of collective human behavior, behavioral models of individual performance, cognitive models involving detailed mechanisms, representations, and processes, as well as biological/physiological models of neural circuits, brain regions, and other detailed biological processes. (shrink)