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  1. Review of Cummins' Representations, Targets, and Attitudes. [REVIEW]Frances Egan - 1998 - Philosophical Review 107 (1):118.
    “Naturalistic” semantic theories attempt to specify, in nonintentional and nonsemantic terms, a sufficient condition for a mental representation’s having a particular meaning. Such theories have trouble accounting for the possibility of representational error. In his latest book, Robert Cummins traces the problem to the fact that the theories currently on offer identify the meaning of a representation with certain features of its use. Only a theory that takes meaning to be an intrinsic feature of a representation, Cummins argues, can both (...)
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  • Artificial Intelligence: The Very Idea.John Haugeland - 1985 - Cambridge: MIT Press.
    The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...
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  • The Computer Revolution in Philosophy: Philosophy, Science, and Models of Mind.Aaron Sloman - 1978 - Hassocks UK: Harvester Press.
    Extract from Hofstadter's revew in Bulletin of American Mathematical Society : http://www.ams.org/journals/bull/1980-02-02/S0273-0979-1980-14752-7/S0273-0979-1980-14752-7.pdf -/- "Aaron Sloman is a man who is convinced that most philosophers and many other students of mind are in dire need of being convinced that there has been a revolution in that field happening right under their noses, and that they had better quickly inform themselves. The revolution is called "Artificial Intelligence" (Al)-and Sloman attempts to impart to others the "enlighten- ment" which he clearly regrets not having (...)
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  • Intentional Systems.Daniel C. Dennett - 1971 - Journal of Philosophy 68 (February):87-106.
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  • A New Look at Habits and the Habit-Goal Interface.Wendy Wood & David T. Neal - 2007 - Psychological Review 114 (4):843-863.
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  • Models of Environment.Marcin Miłkowski - 2016 - In Roger Frantz & Leslie Marsh (eds.), Minds, Models and Milieux. Commemorating the Centennial of the Birth of Herbert Simon. Palgrave-Macmillan. pp. 227-238.
    Herbert A. Simon is well known for his account of bounded rationality. Whereas classical economics idealized economic agency and framed rational choice in terms of the decision theory, Simon insisted that agents need not be optimal in their choices. They might be mere satispcers, i.e., attain good enough goals rather than optimal ones. At the same time, behaviorally as well as computationally, bounded rationality is much more realistic.
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  • The Bounds of Cognition.Sven Walter - 2001 - Philosophical Psychology 14 (2):43-64.
    An alarming number of philosophers and cognitive scientists have argued that mind extends beyond the brain and body. This book evaluates these arguments and suggests that, typically, it does not. A timely and relevant study that exposes the need to develop a more sophisticated theory of cognition, while pointing to a bold new direction in exploring the nature of cognition Articulates and defends the “mark of the cognitive”, a common sense theory used to distinguish between cognitive and non-cognitive processes Challenges (...)
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  • The New Mechanical Philosophy.Stuart Glennan - 2017 - Oxford University Press.
    This volume argues for a new image of science that understands both natural and social phenomena to be the product of mechanisms, casting the work of science as an effort to understand those mechanisms. Glennan offers an account of the nature of mechanisms and of the models used to represent them in physical, life, and social sciences.
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  • Physical Symbol Systems.Allen Newell - 1980 - Cognitive Science 4 (2):135-83.
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  • Neural Computation and the Computational Theory of Cognition.Gualtiero Piccinini & Sonya Bahar - 2013 - Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...)
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  • On Computable Numbers, with an Application to the N Tscheidungsproblem.Alan Turing - 1936 - Proceedings of the London Mathematical Society 42 (1):230-265.
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  • Confirmation, Refutation, and the Evidence of fMRI.Christopher Mole & Colin Klein - 2010 - In Stephen Hanson & Martin Bunzl (eds.), Foundational Issues in Human Brain Mapping. Cambridge: MIT Press. pp. 99.
    This chapter focuses on evidence from functional magnetic resonance imaging data, and discusses the application of neuroimaging techniques to various fields, including cognitive sciences. It considers the role of neuroimaging data in providing informative evidence regarding hypotheses in cognitive science, and explains differences in data, high-level null hypotheses, and ways to accommodate null hypotheses. Finally, the chapter looks into the scope of neuroimaging data in the cognitive sciences.
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  • Fictionalism About Neural Representations.Mark Sprevak - 2013 - The Monist 96 (4):539-560.
    This paper explores a novel form of Mental Fictionalism: Fictionalism about talk of neural representations in cognitive science. This type of Fictionalism promises to (i) avoid the hard problem of naturalising representations, without (ii) incurring the high costs of eliminating useful representation talk. In this paper, I motivate and articulate this form of Fictionalism, and show that, despite its apparent advantages, it faces two serious objections. These objections are: (1) Fictionalism about talk of neural representations ultimately does not avoid the (...)
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  • Measurement-Theoretic Representation and Computation-Theoretic Realization.Eli Dresner - 2010 - Journal of Philosophy 107 (6):275-292.
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  • The False Dichotomy Between Causal Realization and Semantic Computation.Marcin Miłkowski - 2017 - Hybris. Internetowy Magazyn Filozoficzny 38:1-21.
    In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be complemented (...)
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  • Autopoiesis and Cognition: The Realization of the Living.Humberto Muturana, H. R. Maturana & F. J. Varela - 1973/1980 - D. Reidel Publishing Company.
    This is a bold, brilliant, provocative and puzzling work. It demands a radical shift in standpoint, an almost paradoxical posture in which living systems are described in terms of what lies outside the domain of descriptions. Professor Humberto Maturana, with his colleague Francisco Varela, have undertaken the construction of a systematic theoretical biology which attempts to define living systems not as they are objects of observation and description, nor even as in teracting systems, but as self-contained unities whose only reference (...)
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  • The Computer And The Brain.John von Neumann - 1958 - New Haven: Yale University Press.
    This book represents the views of one of the greatest mathematicians of the twentieth century on the analogies between computing machines and the living human brain.
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  • The Symbol Grounding Problem.Stevan Harnad - 1990 - Physica D 42:335-346.
    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 (...)
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  • The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - University of Chicago Press.
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  • Using fMRI to Test Models of Complex Cognition.John R. Anderson, Cameron S. Carter, Jon M. Fincham, Yulin Qin, Susan M. Ravizza & Miriam Rosenberg-Lee - 2008 - Cognitive Science 32 (8):1323-1348.
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  • Tractable Competence.Marcello Frixione - 2001 - Minds and Machines 11 (3):379-397.
    In the study of cognitive processes, limitations on computational resources (computing time and memory space) are usually considered to be beyond the scope of a theory of competence, and to be exclusively relevant to the study of performance. Starting from considerations derived from the theory of computational complexity, in this paper I argue that there are good reasons for claiming that some aspects of resource limitations pertain to the domain of a theory of competence.
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  • The Nature of Explanation. [REVIEW]E. N. & Kenneth J. W. Craik - 1943 - Journal of Philosophy 40 (24):667.
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  • The Rediscovery of the Mind by John Searle. [REVIEW]Daniel C. Dennett - 1993 - Journal of Philosophy 90 (4):193-205.
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  • The Intentional Stance by Daniel Dennett. [REVIEW]Sydney Shoemaker - 1990 - Journal of Philosophy 87 (4):212-216.
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  • Real Patterns.Daniel C. Dennett - 1991 - Journal of Philosophy 88 (1):27-51.
    Are there really beliefs? Or are we learning (from neuroscience and psychology, presumably) that, strictly speaking, beliefs are figments of our imagination, items in a superceded ontology? Philosophers generally regard such ontological questions as admitting just two possible answers: either beliefs exist or they don't. There is no such state as quasi-existence; there are no stable doctrines of semi-realism. Beliefs must either be vindicated along with the viruses or banished along with the banshees. A bracing conviction prevails, then, to the (...)
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  • Minds, Brains, and Programs.John R. Searle - 1980 - Behavioral and Brain Sciences 3 (3):417-57.
    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. (...)
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  • The Bounds of Cognition.Frederick Adams & Kenneth Aizawa - 2008 - Malden, MA, USA: Wiley-Blackwell.
    A critique of the hypothesis of extended cognition.
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  • Predictive Processing and the Representation Wars: A Victory for the Eliminativist.Adrian Downey - 2018 - Synthese 195 (12):5115-5139.
    In this paper I argue that, by combining eliminativist and fictionalist approaches toward the sub-personal representational posits of predictive processing, we arrive at an empirically robust and yet metaphysically innocuous cognitive scientific framework. I begin the paper by providing a non-representational account of the five key posits of predictive processing. Then, I motivate a fictionalist approach toward the remaining indispensable representational posits of predictive processing, and explain how representation can play an epistemologically indispensable role within predictive processing explanations without thereby (...)
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  • Rethinking the Problem of Cognition.Mikio Akagi - 2018 - Synthese 195 (8):3547-3570.
    The present century has seen renewed interest in characterizing cognition, the object of inquiry of the cognitive sciences. In this paper, I describe the problem of cognition—the absence of a positive characterization of cognition despite a felt need for one. It is widely recognized that the problem is motivated by decades of controversy among cognitive scientists over foundational questions, such as whether non-neural parts of the body or environment can realize cognitive processes, or whether plants and microbes have cognitive processes. (...)
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  • Explaining Computation Without Semantics: Keeping It Simple.Nir Fresco - 2010 - Minds and Machines 20 (2):165-181.
    This paper deals with the question: how is computation best individuated? -/- 1. The semantic view of computation: computation is best individuated by its semantic properties. 2. The causal view of computation: computation is best individuated by its causal properties. 3. The functional view of computation: computation is best individuated by its functional properties. -/- Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated (...)
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  • Explanation and Description in Computational Neuroscience.David Michael Kaplan - 2011 - Synthese 183 (3):339-373.
    The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...)
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  • Information for Perception and Information Processing.Anthony Chemero - 2003 - Minds and Machines 13 (4):577-588.
    Do psychologists and computer/cognitive scientists mean the same thing by the term `information'? In this essay, I answer this question by comparing information as understood by Gibsonian, ecological psychologists with information as understood in Barwise and Perry's situation semantics. I argue that, with suitable massaging, these views of information can be brought into line. I end by discussing some issues in (the philosophy of) cognitive science and artificial intelligence.
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  • A Defense of Cartesian Materialism.Jonathan Opie - 1999 - Philosophy and Phenomenological Research 59 (4):939 - 963.
    One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or (...)
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  • The Intentional Stance.Daniel C. Dennett - 1987 - MIT Press.
    Through the use of such "folk" concepts as belief, desire, intention, and expectation, Daniel Dennett asserts in this first full scale presentation of...
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  • A Defense of Cartesian Materialism.Gerard O’Brien & Jonathan Opie - 1999 - Philosophical and Phenomenological Research 59 (4):939-963.
    One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or (...)
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  • Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience.Carl F. Craver - 2007 - Oxford University Press, Clarendon Press.
    Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.
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  • Physical Computation: A Mechanistic Account.Gualtiero Piccinini - 2015 - Oxford University Press UK.
    Gualtiero Piccinini articulates and defends a mechanistic account of concrete, or physical, computation. A physical system is a computing system just in case it is a mechanism one of whose functions is to manipulate vehicles based solely on differences between different portions of the vehicles according to a rule defined over the vehicles. Physical Computation discusses previous accounts of computation and argues that the mechanistic account is better. Many kinds of computation are explicated, such as digital vs. analog, serial vs. (...)
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  • Progress and its Problems: Toward a Theory of Scientific Growth.Larry Laudan - 1977 - University of California Press.
    (This insularity was further promoted by the guileless duplicity of scholars in other fields, who were all too prepared to bequeath "the problem of ...
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  • The Structure of Scientific Revolutions.Thomas Samuel Kuhn - 1962 - Chicago: University of Chicago Press.
    A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. Research (...)
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  • Computation Without Representation.Gualtiero Piccinini - 2008 - Philosophical Studies 137 (2):205-241.
    The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...)
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  • Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective.Marcin Miłkowski - 2016 - Synthese 193 (5):1457-1478.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...)
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  • Structural Representations: Causally Relevant and Different From Detectors.Paweł Gładziejewski & Marcin Miłkowski - 2017 - Biology and Philosophy 32 (3):337-355.
    This paper centers around the notion that internal, mental representations are grounded in structural similarity, i.e., that they are so-called S-representations. We show how S-representations may be causally relevant and argue that they are distinct from mere detectors. First, using the neomechanist theory of explanation and the interventionist account of causal relevance, we provide a precise interpretation of the claim that in S-representations, structural similarity serves as a “fuel of success”, i.e., a relation that is exploitable for the representation using (...)
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  • Toward Analog Neural Computation.Corey Maley - 2018 - Minds and Machines 28 (1):77-91.
    Computationalism about the brain is the view that the brain literally performs computations. For the view to be interesting, we need an account of computation. The most well-developed account of computation is Turing Machine computation, the account provided by theoretical computer science which provides the basis for contemporary digital computers. Some have thought that, given the seemingly-close analogy between the all-or-nothing nature of neural spikes in brains and the binary nature of digital logic, neural computation could be a species of (...)
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  • Minimal Models and Canonical Neural Computations: The Distinctness of Computational Explanation in Neuroscience.M. Chirimuuta - 2014 - Synthese 191 (2):127-153.
    In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...)
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  • Solving the Frame Problem a Mathematical Investigation of the Common Sense Law of Inertia.Murray Shanahan & Professor of Cognitive Robotics Murray Shanahan - 1997 - MIT Press.
    In 1969, John McCarthy and Pat Hayes uncovered a problem that has haunted the field of artificial intelligence ever since--the frame problem. The problem arises when logic is used to describe the effects of actions and events. Put simply, it is the problem of representing what remains unchanged as a result of an action or event. Many researchers in artificial intelligence believe that its solution is vital to the realization of the field's goals. Solving the Frame Problem presents the various (...)
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  • Explaining the Brain.Carl F. Craver - 2009 - Oxford University Press.
    Carl F. Craver investigates what we are doing when we use neuroscience to explain what's going on in the brain. When does an explanation succeed and when does it fail? Craver offers explicit standards for successful explanation of the workings of the brain, on the basis of a systematic view about what neuroscientific explanations are.
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  • Minds, Brains, and Programs.John Searle - 1980 - In John Heil (ed.), Philosophy of Mind: A Guide and Anthology. Oxford University Press.
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  • The Rediscovery of the Mind.John Searle - 1992 - MIT Press.
    The title of The Rediscovery of the Mind suggests the question "When was the mind lost?" Since most people may not be aware that it ever was lost, we must also then ask "Who lost it?" It was lost, of course, only by philosophers, by certain philosophers. This passed unnoticed by society at large. The "rediscovery" is also likely to pass unnoticed. But has the mind been rediscovered by the same philosophers who "lost" it? Probably not. John Searle is an (...)
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  • Computation and Cognition: Toward a Foundation for Cognitive Science.Zenon W. Pylyshyn - 1984 - MIT Press.
    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 (...)
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  • Representation Reconsidered.William M. Ramsey - 2007 - Cambridge University Press.
    Cognitive representation is the single most important explanatory notion in the sciences of the mind and has served as the cornerstone for the so-called 'cognitive revolution'. This book critically examines the ways in which philosophers and cognitive scientists appeal to representations in their theories, and argues that there is considerable confusion about the nature of representational states. This has led to an excessive over-application of the notion - especially in many of the fresher theories in computational neuroscience. Representation Reconsidered shows (...)
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