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  1. Explaining Behavior: Reasons in a World of Causes.Fred I. Dretske - 1988 - MIT Press.
    In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.
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  • Knowledge and the Flow of Information.Fred I. Dretske - 1981 - Stanford, CA: MIT Press.
    This book presents an attempt to develop a theory of knowledge and a philosophy of mind using ideas derived from the mathematical theory of communication developed by Claude Shannon. Information is seen as an objective commodity defined by the dependency relations between distinct events. Knowledge is then analyzed as information caused belief. Perception is the delivery of information in analog form for conceptual utilization by cognitive mechanisms. The final chapters attempt to develop a theory of meaning by viewing meaning as (...)
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  • (1 other version)Meaning.Herbert Paul Grice - 1957 - Philosophical Review 66 (3):377-388.
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  • Connectionism and cognitive architecture: A critical analysis.Jerry A. Fodor & Zenon W. Pylyshyn - 1988 - Cognition 28 (1-2):3-71.
    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 (...)
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  • A Theory of Content and Other Essays.Jerry A. Fodor - 1990 - MIT Press.
    Preface and Acknowledgments Introduction PART I Intentionality Chapter 1 Fodor’ Guide to Mental Representation: The Intelligent Auntie’s Vade-Mecum Chapter 2 Semantics, Wisconsin Style Chapter 3 A Theory of Content, I: The Problem Chapter 4 A Theory of Content, II: The Theory Chapter 5 Making Mind Matter More Chapter 6 Substitution Arguments and the Individuation of Beliefs Chapter 7 Stephen Schiffer’s Dark Night of The Soul: A Review of Remnants of Meaning PART II Modularity Chapter 8 Précis of The Modularity of (...)
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  • (1 other version)The magical number seven, plus or minus two: Some limits on our capacity for processing information.George A. Miller - 1956 - Psychological Review 63 (2):81-97.
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  • Varieties of Meaning: The 2002 Jean Nicod Lectures.Ruth Garrett Millikan - 2004 - MIT Press.
    How the various things that are said to have meaning—purpose, natural signs, linguistic signs, perceptions, and thoughts—are related to one another.
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  • On Computable Numbers, with an Application to the Entscheidungsproblem.Alan Turing - 1936 - Proceedings of the London Mathematical Society 42 (1):230-265.
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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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  • (1 other version)A logical calculus of the ideas immanent in nervous activity.Warren S. McCulloch & Walter Pitts - 1943 - The Bulletin of Mathematical Biophysics 5 (4):115-133.
    Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes. It is shown that many particular choices among possible neurophysiological assumptions (...)
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  • (1 other version)Knowledge and the Flow of Information.Fred I. Dretske - 1981 - Revue Philosophique de la France Et de l'Etranger 175 (1):69-70.
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  • What Might Cognition Be, If Not Computation?Tim Van Gelder - 1995 - Journal of Philosophy 92 (7):345 - 381.
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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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  • Cybernetics or Control and Communication in the Animal and the Machine.N. Wiener - 1948 - Revue Philosophique de la France Et de l'Etranger 141:578-580.
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  • From Folk Psychology to Cognitive Science.Stephen Stich - 1986 - Philosophical Quarterly 36 (143):261-278.
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  • Information Flow: The Logic of Distributed Systems.Jon Barwise & Jerry Seligman - 1997 - Cambridge University Press.
    Presents a mathematically rigorous, philosophically sound foundation for a science of information.
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  • (1 other version)The mind-body problem.Jerry Fodor - 1981 - Scientific American 244 (1):114-25.
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  • (1 other version)The magical number seven, plus or minus two: Some limits on our capacity for processing information.George A. Miller - 1956 - Psychological Review 101 (2):343-352.
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  • Design for a Brain.W. Ross Ashby - 1953 - British Journal for the Philosophy of Science 4 (14):169-173.
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  • Towards a causal theory of linguistic representation.Dennis W. Stampe - 1977 - Midwest Studies in Philosophy 2 (1):42-63.
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  • (1 other version)A Logical Calculus of the Ideas Immanent in Nervous Activity.Warren S. Mcculloch & Walter Pitts - 1943 - Journal of Symbolic Logic 9 (2):49-50.
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  • Behavior, purpose and teleology.Arturo Rosenblueth, Norbert Wiener & Julian Bigelow - 1943 - Philosophy of Science 10 (1):18-24.
    This essay has two goals. The first is to define the behavioristic study of natural events and to classify behavior. The second is to stress the importance of the concept of purpose.Given any object, relatively abstracted from its surroundings for study, the behavioristic approach consists in the examination of the output of the object and of the relations of this output to the input. By output is meant any change produced in the surroundings by the object. By input, conversely, is (...)
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  • An Unsolvable Problem of Elementary Number Theory.Alonzo Church - 1936 - Journal of Symbolic Logic 1 (2):73-74.
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  • Is semantic information meaningful data?Luciano Floridi - 2005 - Philosophy and Phenomenological Research 70 (2):351-370.
    There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on (...)
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  • A Mathematical Theory of Communication.Claude Elwood Shannon - 1948 - Bell System Technical Journal 27 (April 1924):379–423.
    The mathematical theory of communication.
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  • (Nonsolipsistic) conceptual role semantics.Gilbert Harman - 1987 - In Ernest LePore (ed.), New directions in semantics. Orlando: Academic Press. pp. 55–81.
    CRS says that the meanings of expressions of a language or other symbol system or the contents of mental states are determined and explained by the way symbols are used in thinking. According to CRS one.
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  • (1 other version)From Folk Psychology to Cognitive Science: The Case against Belief.Stephen P. Stich - 1983 - Behaviorism 14 (2):159-182.
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  • Computing mechanisms.Gualtiero Piccinini - 2007 - Philosophy of Science 74 (4):501-526.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...)
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  • Computation without representation.Gualtiero Piccinini - 2004 - 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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  • A Theory of Content and Other Essays.Alan Millar - 1992 - Philosophical Quarterly 42 (168):367-372.
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  • Theoretical neuroscience: computational and mathematical modeling of neural systems.Peter Dayan & L. Abbott - 2001 - Philosophical Psychology 15 (4):563-577.
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  • Neurophilosophy at Work.Paul M. Churchland - 2007 - New York: Cambridge University Press.
    Churchland explores the unfolding impact of the several empirical sciences of the mind, especially cognitive neurobiology and computational neuroscience on a variety of traditional issues central to the discipline of philosophy. Representing Churchland's most recent research, they continue his research program, launched over thirty years ago which has evolved into the field of neurophilosophy. Topics such as the nature of Consciousness, the nature of cognition and intelligence, the nature of moral knowledge and moral reasoning, neurosemantics or world-representation in the brain, (...)
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  • Knowledge and the Flow of Information.J. Christopher Maloney - 1985 - Noûs 19 (2):299-306.
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  • Finite combinatory processes—formulation.Emil L. Post - 1936 - Journal of Symbolic Logic 1 (3):103-105.
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  • (1 other version)The Mind-Body Problem.Jerry Fodor - 2003 - In John Heil (ed.), Philosophy of Mind: A Guide and Anthology. New York: Oxford University Press.
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  • (1 other version)Functionalism, computationalism, and mental contents.Gualtiero Piccinini - 2004 - Canadian Journal of Philosophy 34 (3):375-410.
    Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.
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  • (1 other version)Functionalism, Computationalism, & Mental States.Gualtiero Piccinini - 2004 - Studies in History and Philosophy of Science 35 (4):811-833.
    Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.
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  • Computability, Complexity and Languages.Martin Davies, Ron Segal & Elaine Weyuker - 1994 - Academic Press.
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  • The first computational theory of mind and brain: A close look at McCulloch and Pitts' Logical Calculus of Ideas Immanent in Nervous Activity.Gualtiero Piccinini - 2004 - Synthese 141 (2):175-215.
    Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in (...)
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  • Computers.Gualtiero Piccinini - 2008 - Pacific Philosophical Quarterly 89 (1):32–73.
    I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system's mechanistic (...)
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  • Neurophilosophy at Work.Paul Churchland - 2009 - Analysis 69 (1):176-178.
    This is a collection of Paul Churchland's recent essays which have in common an overarching research programme aimed at identifying the scope and the importance of the contributions that neuroscience has made and will make to philosophy of mind, moral philosophy, epistemology and metaphysics. The general structure of many of the essays included in the collection is as follows: there is a long-standing problem in the philosophical literature which has escaped not only a convincing solution but also a straightforward analysis (...)
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  • (1 other version)Computational explanation and mechanistic explanation of mind.Gualtiero Piccinini - 2007 - In Francesco Ferretti, Massimo Marraffa & Mario De Caro (eds.), Cartographies of the Mind: The Interface between Philosophy and Cognitive Science. Springer. pp. 343-353.
    According to the computational theory of mind (CTM), mental capacities are explained by inner computations, which in biological organisms are realized in the brain. Computational explanation is so popular and entrenched that it’s common for scientists and philosophers to assume CTM without argument.
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  • The Introduction of Information into Neurobiology.Justin Garson - 2003 - Philosophy of Science 70 (5):926-936.
    The first use of the term "information" to describe the content of nervous impulse occurs 20 years prior to Shannon`s (1948) work, in Edgar Adrian`s The Basis of Sensation (1928). Although, at least throughout the 1920s and early 30s, the term "information" does not appear in Adrian`s scientific writings to describe the content of nervous impulse, the notion that the structure of nervous impulse constitutes a type of message subject to certain constraints plays an important role in all of his (...)
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  • An objective counterfactual theory of information.Jonathan Cohen & Aaron Meskin - 2006 - Australasian Journal of Philosophy 84 (3):333 – 352.
    We offer a novel theory of information that differs from traditional accounts in two respects: (i) it explains information in terms of counterfactuals rather than conditional probabilities, and (ii) it does not make essential reference to doxastic states of subjects, and consequently allows for the sort of objective, reductive explanations of various notions in epistemology and philosophy of mind that many have wanted from an account of information.
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  • A New Kind of Science.Stephen Wolfram - 2002 - Bulletin of Symbolic Logic 10 (1):112-114.
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  • (1 other version)The foundations of computing.Brian Cantwell Smith - 2002 - In Matthias Scheutz (ed.), Computationalism: New Directions. MIT Press.
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  • Some Neural Networks Compute, Others Don't.Gualtiero Piccinini - 2008 - Neural Networks 21 (2-3):311-321.
    I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend
    the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way.
    Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks
    compute in a non-classical way. (4) Yet other neural networks do not perform computations. Brains may well fall into this last class.
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  • Automata Studies.John Mccarthy & Claude Shannon - 1958 - Journal of Symbolic Logic 23 (1):59-60.
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  • Information and belief.Barry Loewer - 1983 - Behavioral and Brain Sciences 6 (1):75-76.
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  • Shell games, information, and counterfactuals.Andrea Scarantino - 2008 - Australasian Journal of Philosophy 86 (4):629 – 634.
    Cohen and Meskin 2006 have recently proposed a novel counterfactual account of information. I argue that it is a step down from its intended target, namely Dretske's 1981 theory of information. Thinking of the information carried by signals in terms of counterfactuals leads to falsely diagnosing bona fide instances of information transmission as not being instances of information transmission at all, with major loss of explanatory power.
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