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  1. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Judea Pearl - 1988 - Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  • Scientific reasoning: the Bayesian approach.Peter Urbach & Colin Howson - 1993 - Chicago: Open Court. Edited by Peter Urbach.
    Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...
  • Philosophy of natural science.Carl Gustav Hempel - 1966 - Englewood Cliffs, N.J.,: Prentice-Hall.
  • Similarity, separability, and the triangle inequality.Amos Tversky & Itamar Gati - 1982 - Psychological Review 89 (2):123-154.
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  • Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.Amos Tversky & Daniel Kahneman - 1983 - Psychological Review 90 (4):293-315.
  • Features of similarity.Amos Tversky - 1977 - Psychological Review 84 (4):327-352.
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  • Judgment under Uncertainty: Heuristics and Biases.Amos Tversky & Daniel Kahneman - 1974 - Science 185 (4157):1124-1131.
    This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...)
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  • Similarity, plausibility, and judgments of probability.E. Smith - 1993 - Cognition 49 (1-2):67-96.
  • Combining Prototypes: A Selective Modification Model.Edward E. Smith, Daniel N. Osherson, Lance J. Rips & Margaret Keane - 1988 - Cognitive Science 12 (4):485-527.
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference by Judea Pearl. [REVIEW]Henry E. Kyburg - 1991 - Journal of Philosophy 88 (8):434-437.
  • Category-based induction.Daniel N. Osherson, Edward E. Smith, Ormond Wilkie & Alejandro López - 1990 - Psychological Review 97 (2):185-200.
  • Default Probability.Daniel N. Osherson, Joshua Stern, Ormond Wilkie, Michael Stob & Edward E. Smith - 1991 - Cognitive Science 15 (2):251-269.
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  • Ampliative inference: on choosing a probability distribution.D. Osherson - 1993 - Cognition 49 (3):189-210.
  • Probability and Evidence by Paul Horwich. [REVIEW]Stephen Spielman - 1984 - Journal of Philosophy 81 (3):168-173.
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  • A spreading-activation theory of semantic processing.Allan M. Collins & Elizabeth F. Loftus - 1975 - Psychological Review 82 (6):407-428.
  • An Overview of KRL, a Knowledge Representation Language.Daniel G. Bobrow & Terry Winograd - 1977 - Cognitive Science 1 (1):3-46.
    This paper describes KRL, a Knowledge Representation Language designed for use in understander systems. It outlines both the general concepts which underlie our research and the details of KRL‐0, an experimental implementation of some of these concepts. KRL is an attempt to integrate procedural knowledge with a broad base of declarative forms. These forms provide a variety of ways to express the logical structure of the knowledge, in order to give flexibility in associating procedures (for memory and reasoning) with specific (...)
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  • Categories and Concepts.Edward E. Smith & L. Douglas - 1981 - Harvard University Press.
  • The Society Of Mind.Marvin Minsky - 1986 - Simon & Schuster.
    Computing Methodologies -- Artificial Intelligence.
  • Judgment Under Uncertainty: Heuristics and Biases.Daniel Kahneman, Paul Slovic & Amos Tversky (eds.) - 1982 - Cambridge University Press.
    The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important...
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  • Probability and Evidence.Paul Horwich - 1982 - Cambridge: Cambridge University Press.
    In this influential study of central issues in the philosophy of science, Paul Horwich elaborates on an important conception of probability, diagnosing the failure of previous attempts to resolve these issues as stemming from a too-rigid conception of belief. Adopting a Bayesian strategy, he argues for a probabilistic approach, yielding a more complete understanding of the characteristics of scientific reasoning and methodology. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Colin Howson, illuminating its (...)
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  • The Society of Mind.Marvin Minsky - 1987 - The Personalist Forum 3 (1):19-32.
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  • A Framework for Representing Knowledge.Marvin Minsky - unknown
    It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities.
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  • Similarity and Property Effects in Inductive Reasoning.Evan Heit & Joshua Rubinstein - 1994 - Journal of Experimental Psychology 20:411-422.