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  1. Computing Machinery and Intelligence.Alan M. Turing - 1950 - Mind 59 (October):433-60.
    I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...)
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  • Being-in-the-World: A Commentary on Heidegger's Being in Time, Division I.Hubert L. Dreyfus - 1990 - Bradford.
    Essays discuss the themes of worldliness, affectedness, understanding, and the care-structure found in Heidegger's work on the nature of existence.
  • 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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  • Intrinsic Intentionality.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):450-457.
  • Facing Up to the Problem of Consciousness.David J. Chalmers - 1995 - Journal of Consciousness Studies 2 (3):200-19.
    To make progress on the problem of consciousness, we have to confront it directly. In this paper, I first isolate the truly hard part of the problem, separating it from more tractable parts and giving an account of why it is so difficult to explain. I critique some recent work that uses reductive methods to address consciousness, and argue that such methods inevitably fail to come to grips with the hardest part of the problem. Once this failure is recognized, the (...)
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  • Hubert L. Dreyfus’s Critique of Classical AI and its Rationalist Assumptions.Setargew Kenaw - 2008 - Minds and Machines 18 (2):227-238.
    This paper deals with the rationalist assumptions behind researches of artificial intelligence (AI) on the basis of Hubert Dreyfus’s critique. Dreyfus is a leading American philosopher known for his rigorous critique on the underlying assumptions of the field of artificial intelligence. Artificial intelligence specialists, especially those whose view is commonly dubbed as “classical AI,” assume that creating a thinking machine like the human brain is not a too far away project because they believe that human intelligence works on the basis (...)
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  • Shedding Computational Light on Human Creativity.Subrata Dasgupta - 2008 - Perspectives on Science 16 (2):pp. 121-136.
    Ever since 1956 when details of the Logic Theorist were published by Newell and Simon, a large literature has accumulated on computational models and theories of the creative process, especially in science, invention and design. But what exactly do these computational models/theories tell us about the way that humans have actually conducted acts of creation in the past? What light has computation shed on our understanding of the creative process? Addressing these questions, we put forth three propositions: (I) Computational models (...)
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  • More Things Than Are Dreamt of in Your Biology: Information-Processing in Biologically Inspired Robots.A. Sloman & R. L. Chrisley - unknown
    Animals and robots perceiving and acting in a world require an ontology that accommodates entities, processes, states of affairs, etc., in their environment. If the perceived environment includes information - processing systems, the ontology should reflect that. Scientists studying such systems need an ontology that includes the first - order ontology characterising physical phenomena, the second - order ontology characterising perceivers of physical phenomena, and a third order ontology characterising perceivers of perceivers, including introspectors. We argue that second - and (...)
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  • The Emperor's New Mind.Roger Penrose - 1989 - Oxford University Press.
    Winner of the Wolf Prize for his contribution to our understanding of the universe, Penrose takes on the question of whether artificial intelligence will ever ...
  • ELIZA—A Computer Program For the Study of Natural Language Communication Between Man And Machine.Joseph Weizenbaum - 1966 - Communications of the Acm 9 (1):36-45.
     
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  • Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I.K. Gödel - 1931 - Monatshefte für Mathematik 38 (1):173--198.
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  • The Creative Mind: Myths and Mechanisms.Margaret A. Boden - 2003 - Routledge.
    How is it possible to think new thoughts? What is creativity and can science explain it? And just how did Coleridge dream up the creatures of The Ancient Mariner? When The Creative Mind: Myths and Mechanisms was first published, Margaret A. Boden's bold and provocative exploration of creativity broke new ground. Boden uses examples such as jazz improvisation, chess, story writing, physics, and the music of Mozart, together with computing models from the field of artificial intelligence to uncover the nature (...)
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  • The Knowledge Level.Allen Newell - 1982 - Artificial Intelligence 18:81-132.
  • Gödel's Theorem. An Incomplete Guide to its Use and Abuse.Torkel Franzén - 2005 - A K Peters.
     
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  • What Computers Still Can't Do.Hubert 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.
  • The Sciences of the Artificial.Herbert A. Simon - 1969 - [Cambridge, M.I.T. Press.
    Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...
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