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  1. Perceptual symbol systems.Lawrence W. Barsalou - 1999 - Behavioral and Brain Sciences 22 (4):577-660.
    Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...)
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  • I Am a Strange Loop.Douglas R. Hofstadter - 2007 - New York, NY, USA: Basic Books.
    Can thought arise out of matter? Can self, soul, consciousness, “I” arise out of mere matter? If it cannot, then how can you or I be here? I Am a Strange Loop argues that the key to understanding selves and consciousness is the “strange loop”—a special kind of abstract feedback loop inhabiting our brains. The most central and complex symbol in your brain is the one called “I.” The “I” is the nexus in our brain, one of many symbols seeming (...)
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  • Artificial intelligence.Stuart C. Shapiro - 1976 - Artificial Intelligence 7 (2):199-201.
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  • (1 other version)Computer Science as Empirical Inquiry: Symbols and Search.Allen Newell & H. A. Simon - 1976 - Communications of the Acm 19:113-126.
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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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  • Semiotic Machine.Mihai Nadin - unknown
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  • (1 other version)Minds, Brains, and Programs.John Searle - 2003 - In John Heil (ed.), Philosophy of Mind: A Guide and Anthology. New York: Oxford University Press.
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  • (1 other version)Computing Machinery and Intelligence.Alan M. Turing - 2003 - In John Heil (ed.), Philosophy of Mind: A Guide and Anthology. New York: Oxford University Press.
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  • (1 other version)Minds, Machines and Gödel.John R. Lucas - 1961 - Philosophy 36 (137):112-127.
    Gödei's Theorem seems to me to prove that Mechanism is false, that is, that minds cannot be explained as machines. So also has it seemed to many other people: almost every mathematical logician I have put the matter to has confessed to similar thoughts, but has felt reluctant to commit himself definitely until he could see the whole argument set out, with all objections fully stated and properly met. This I attempt to do.
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  • Implementation is Semantic Interpretation.Willam J. Rapaport - 1999 - The Monist 82 (1):109-130.
    What is the computational notion of “implementation”? It is not individuation, instantiation, reduction, or supervenience. It is, I suggest, semantic interpretation.
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  • Seeing What is not There.Gabriel Segal - 1989 - Philosophical Review 98 (2):189.
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  • (1 other version)Mental Reality. 2nd edition.Galen Strawson - unknown
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  • Rational choice and the structure of the environment.Herbert A. Simon - 1955 - Psychological Review 63 (2):129-138.
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  • Foundations of Language: Brain, Meaning, Grammar, Evolution.Ray Jackendoff - 2002 - Oxford University Press UK.
    Presenting a landmark in linguistics and cognitive science, Ray Jackendoff proposes a new holistic theory of the relation between the sounds, structure, and meaning of language and their relation to mind and brain. Foundations of Language exhibits the most fundamental new thinking in linguistics since Noam Chomsky's Aspects of the Theory of Syntax in 1965—yet is readable, stylish, and accessible to a wide readership. Along the way it provides new insights on the evolution of language, thought, and communication.
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  • (1 other version)Minds, Machines and Gödel.J. R. Lucas - 1961 - Etica E Politica 5 (1):1.
    In this article, Lucas maintains the falseness of Mechanism - the attempt to explain minds as machines - by means of Incompleteness Theorem of Gödel. Gödel’s theorem shows that in any system consistent and adequate for simple arithmetic there are formulae which cannot be proved in the system but that human minds can recognize as true; Lucas points out in his turn that Gödel’s theorem applies to machines because a machine is the concrete instantiation of a formal system: therefore, for (...)
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  • What Computers Still Can’T Do: A Critique of Artificial Reason.Hubert L. Dreyfus - 1992 - MIT Press.
    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.
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  • How to make the World Fit Our Language.Wüliam J. Rapaport - 1981 - Grazer Philosophische Studien 14:1-21.
    Natural languages differ from most formal languages in having a partial, rather than a total, semantic interpretation function; e.g., some noun phrases don't refer. The usual semantics for handling such noun phrases (e.g., Russell, Quine) require syntactic reform. The alternative presented here is semantic expansion, viz., enlarging the range of the interpretaion function to make it total. A specific ontology based on Meinong's Theory of Objects, which can serve as domain on interpretation, is suggested, and related to the work of (...)
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  • Methodological solipsism considered as a research strategy in cognitive psychology.Jerry A. Fodor - 1979 - Behavioral and Brain Sciences 3 (1):63-73.
    The paper explores the distinction between two doctrines, both of which inform theory construction in much of modern cognitive psychology: the representational theory of mind and the computational theory of mind. According to the former, propositional attitudes are to be construed as relations that organisms bear to mental representations. According to the latter, mental processes have access only to formal (nonsemantic) properties of the mental representations over which they are defined.The following claims are defended: (1) That the traditional dispute between (...)
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  • Introduction.Barry Smith & David Woodruff Smith - 1995 - In Barry Smith & David Woodruff Smith (eds.), The Cambridge companion to Husserl. New York: Cambridge University Press.
    Husserl’s philosophy, by the usual account, evolved through three stages: 1. development of an anti-psychologistic, objective foundation of logic and mathematics, rooted in Brentanian descriptive psychology; 2. development of a new discipline of "phenomenology" founded on a metaphysical position dubbed "transcendental idealism"; transformation of phenomenology from a form of methodological solipsism into a phenomenology of intersubjectivity and ultimately (in his Crisis of 1936) into an ontology of the life-world, embracing the social worlds of culture and history. We show that this (...)
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  • Contextual Vocabulary Acquisition: from Algorithm to Curriculum.Michael W. Kibby & William J. Rapaport - 2014 - In Michael W. Kibby & William J. Rapaport (eds.), Contextual Vocabulary Acquisition: from Algorithm to Curriculum. pp. 107-150.
    Deliberate contextual vocabulary acquisition (CVA) is a reader’s ability to figure out a (not the) meaning for an unknown word from its “context”, without external sources of help such as dictionaries or people. The appropriate context for such CVA is the “belief-revised integration” of the reader’s prior knowledge with the reader’s “internalization” of the text. We discuss unwarranted assumptions behind some classic objections to CVA, and present and defend a computational theory of CVA that we have adapted to a new (...)
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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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  • What Is the “Context” for Contextual Vocabulary Acquisition?William J. Rapaport - 2003 - Proceedings of the 4th Joint International Conference on Cognitive Science/7th Australasian Society for Cognitive Science Conference 2:547-552.
    “Contextual” vocabulary acquisition is the active, deliberate acquisition of a meaning for a word in a text by reasoning from textual clues and prior knowledge, including language knowledge and hypotheses developed from prior encounters with the word, but without external sources of help such as dictionaries or people. But what is “context”? Is it just the surrounding text? Does it include the reader’s background knowledge? I argue that the appropriate context for contextual vocabulary acquisition is the reader’s “internalization” of the (...)
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  • Lot 2: The Language of Thought Revisited.Jerry A. Fodor - 2008 - New York: Oxford University Press. Edited by Jerry A. Fodor.
    Jerry Fodor presents a new development of his famous Language of Thought hypothesis, which has since the 1970s been at the centre of interdisciplinary debate about how the mind works. Fodor defends and extends the groundbreaking idea that thinking is couched in a symbolic system realized in the brain. This idea is central to the representational theory of mind which Fodor has established as a key reference point in modern philosophy, psychology, and cognitive science. The foundation stone of our present (...)
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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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  • Introduction to metamathematics.Stephen Cole Kleene - 1952 - Groningen: P. Noordhoff N.V..
    Stephen Cole Kleene was one of the greatest logicians of the twentieth century and this book is the influential textbook he wrote to teach the subject to the next generation. It was first published in 1952, some twenty years after the publication of Godel's paper on the incompleteness of arithmetic, which marked, if not the beginning of modern logic. The 1930s was a time of creativity and ferment in the subject, when the notion of computable moved from the realm of (...)
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  • (15 other versions)Leviathan.Thomas Hobbes - 1936 - Harmondsworth,: Penguin Books. Edited by C. B. Macpherson.
    v. 1. Editorial introduction -- v. 2. The English and Latin texts (i) -- v. 3. The English and Latin texts (ii).
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  • Darwin's ''strange inversion of reasoning''.Daniel Dennett - unknown
    Darwin’s theory of evolution by natural selection unifies the world of physics with the world of meaning and purpose by proposing a deeply counterintuitive ‘‘inversion of reasoning’’ (according to a 19th century critic): ‘‘to make a perfect and beautiful machine, it is not requisite to know how to make it’’ [MacKenzie RB (1868) (Nisbet & Co., London)]. Turing proposed a similar inversion: to be a perfect and beautiful computing machine, it is not requisite to know what arithmetic is. Together, these (...)
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  • Computing the Mind: How the Mind Really Works.Shimon Edelman - 2008 - Oxford University Press.
    The account that Edelman gives in this book is accessible, yet unified and rigorous, and the big picture he presents is supported by evidence ranging from ...
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  • The Work of the Imagination.Paul L. Harris - 2000 - Wiley-Blackwell.
    This book demonstrates how children's imagination makes a continuing contribution to their cognitive and emotional development.
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  • (2 other versions)An enquiry concerning human understanding.David Hume - 2000 - In Steven M. Cahn (ed.), Exploring Philosophy: An Introductory Anthology. New York, NY, United States of America: Oxford University Press USA. pp. 112.
    David Hume's Enquiry concerning Human Understanding is the definitive statement of the greatest philosopher in the English language. His arguments in support of reasoning from experience, and against the "sophistry and illusion"of religiously inspired philosophical fantasies, caused controversy in the eighteenth century and are strikingly relevant today, when faith and science continue to clash. The Enquiry considers the origin and processes of human thought, reaching the stark conclusion that we can have no ultimate understanding of the physical world, or indeed (...)
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  • (3 other versions)Leviathan.Thomas Hobbes - 2007 - In Aloysius Martinich, Fritz Allhoff & Anand Vaidya (eds.), Early Modern Philosophy: Essential Readings with Commentary. Oxford: Wiley-Blackwell.
    Thomas Hobbes took a new look at the ways in which society should function, and he ended up formulating the concept of political science. His crowning achievement, Leviathan, remains among the greatest works in the history of ideas. Written during a moment in English history when the political and social structures as well as methods of science were in flux and open to interpretation, Leviathan played an essential role in the development of the modern world. This edition of Hobbes' landmark (...)
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  • (2 other versions)Mathematical Logic.Mariko Yasugi - 1967 - Journal of Symbolic Logic 35 (3):438-440.
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  • (2 other versions)Introduction to Metamathematics.Ann Singleterry Ferebee - 1968 - Journal of Symbolic Logic 33 (2):290-291.
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  • True grid.Barry Smith - 2001 - In Daniel R. Montello (ed.), Spatial Information Theory: Foundations of Geographic Information Science. New York: Springer. pp. 14-27.
    The Renaissance architect, moral philosopher, cryptographer, mathematician, Papal adviser, painter, city planner and land surveyor Leon Battista Alberti provided the theoretical foundations of modern perspective geometry. Alberti’s work on perspective exerted a powerful influence on painters of the stature of Albrecht Dürer, Leonardo da Vinci and Piero della Francesca. But his Della pittura of 1435–36 contains also a hitherto unrecognized ontology of pictorial projection. We sketch this ontology, and show how it can be generalized to apply to representative devices in (...)
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  • (2 other versions)The semantic conception of truth and the foundations of semantics.Alfred Tarski - 1943 - Philosophy and Phenomenological Research 4 (3):341-376.
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  • (1 other version)Hot Thought: Mechanisms and Applications of Emotional Cognition.Paul Thagard - 2006 - Cambridge MA: Bradford Book/MIT Press.
    A description of mental mechanisms that explain how emotions influence thought, from everyday decision making to scientific discovery and religious belief, and an analysis of when emotion can contribute to good reasoning.
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  • Daydreaming in Humans and Machines: A Computer Model of the Stream of Thought.Erik T. Mueller - 1990 - Ablex.
    Chapter Introduction The field of artificial intelligence is concerned with the construction of computer systems which exhibit intelligent behavior in order ...
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  • (1 other version)Situated action: A symbolic interpretation.A. H. Vera & Herbert A. Simon - 1993 - Cognitive Science 17 (1):7-48.
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  • Understanding Computers and Cognition: A New Foundation for Design.Terry Winograd & Fernando Flores - 1987 - Addison-Wesley.
    Understanding Computers and Cognition presents an important and controversial new approach to understanding what computers do and how their functioning is related to human language, thought, and action. While it is a book about computers, Understanding Computers and Cognition goes beyond the specific issues of what computers can or can't do. It is a broad-ranging discussion exploring the background of understanding in which the discourse about computers and technology takes place. Understanding Computers and Cognition is written for a wide audience, (...)
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  • Artificial Intelligence: Its Scope and Limits.James H. Fetzer - 1990 - Kluwer Academic Publishers.
    1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..
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  • Models and minds.Stuart C. Shapiro & William J. Rapaport - 1991 - In Robert C. Cummins (ed.), Philosophy and AI: Essays at the Interface. Cambridge: MIT Press. pp. 215--259.
    Cognitive agents, whether human or computer, that engage in natural-language discourse and that have beliefs about the beliefs of other cognitive agents must be able to represent objects the way they believe them to be and the way they believe others believe them to be. They must be able to represent other cognitive agents both as objects of beliefs and as agents of beliefs. They must be able to represent their own beliefs, and they must be able to represent beliefs (...)
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  • Computationalism.Eric Dietrich - 1990 - Social Epistemology 4 (2):135-154.
    This paper argues for a noncognitiveist computationalism in the philosophy of mind. It further argues that both humans and computers have intentionality, that is, their mental states are semantical -- they are about things in their worlds.
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  • The computational theory of mind.Steven Horst - 2005 - Stanford Encyclopedia of Philosophy.
    Over the past thirty years, it is been common to hear the mind likened to a digital computer. This essay is concerned with a particular philosophical view that holds that the mind literally is a digital computer (in a specific sense of “computer” to be developed), and that thought literally is a kind of computation. This view—which will be called the “Computational Theory of Mind” (CTM)—is thus to be distinguished from other and broader attempts to connect the mind with computation, (...)
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  • (1 other version)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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  • (1 other version)Computer science as empirical inquiry: Symbols and search.Allen Newell & Herbert A. Simon - 1981 - Communications of the Association for Computing Machinery 19:113-26.
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  • Syntactic semantics: Foundations of computational natural language understanding.William J. Rapaport - 1988 - In James H. Fetzer (ed.), Aspects of AI. D.
    This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are discussed, and (...)
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  • Understanding understanding: Syntactic semantics and computational cognition.William J. Rapaport - 1995 - Philosophical Perspectives 9:49-88.
    John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: Everything (...)
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  • Computing machines can't be intelligent (...And Turing said so).Peter Kugel - 2002 - Minds and Machines 12 (4):563-579.
    According to the conventional wisdom, Turing said that computing machines can be intelligent. I don't believe it. I think that what Turing really said was that computing machines –- computers limited to computing –- can only fake intelligence. If we want computers to become genuinelyintelligent, we will have to give them enough “initiative” to do more than compute. In this paper, I want to try to develop this idea. I want to explain how giving computers more ``initiative'' can allow them (...)
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  • What Computers Can’T Do: The Limits of Artificial Intelligence.Hubert L. Dreyfus - 1972 - Harper & Row.
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  • (1 other version)Minds, brains, and programs.John 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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