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Machine discovery

Foundations of Science 1 (2):171-200 (1995)

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  1. (4 other versions)The logic of scientific discovery.Karl Raimund Popper - 1934 - New York: Routledge. Edited by Hutchinson Publishing Group.
    Described by the philosopher A.J. Ayer as a work of 'great originality and power', this book revolutionized contemporary thinking on science and knowledge. Ideas such as the now legendary doctrine of 'falsificationism' electrified the scientific community, influencing even working scientists, as well as post-war philosophy. This astonishing work ranks alongside The Open Society and Its Enemies as one of Popper's most enduring books and contains insights and arguments that demand to be read to this day.
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  • Logic, semantics, metamathematics.Alfred Tarski - 1956 - Oxford,: Clarendon Press. Edited by John Corcoran & J. H. Woodger.
    I ON THE PRIMITIVE TERM OF LOGISTICf IN this article I propose to establish a theorem belonging to logistic concerning some connexions, not widely known, ...
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  • (4 other versions)The Logic of Scientific Discovery.K. Popper - 1959 - British Journal for the Philosophy of Science 10 (37):55-57.
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  • Placental Transfer and Synthesis of Hormones.John H. Holland - 1973
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  • (1 other version)Mathematics and plausible reasoning.George Pólya - 1968 - Princeton, N.J.,: Princeton University Press.
    2014 Reprint of 1954 American Edition. Full facsimile of the original edition, not reproduced with Optical Recognition Software. This two volume classic comprises two titles: "Patterns of Plausible Inference" and "Induction and Analogy in Mathematics." This is a guide to the practical art of plausible reasoning, particularly in mathematics, but also in every field of human activity. Using mathematics as the example par excellence, Polya shows how even the most rigorous deductive discipline is heavily dependent on techniques of guessing, inductive (...)
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  • The Processes of Scientific Discovery: The Strategy of Experimentation.Deepak Kulkarni & Herbert A. Simon - 1988 - Cognitive Science 12 (2):139-175.
    Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain‐specific are (...)
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  • Scientific discovery.Pat Langley, Herbert A. Simon, Gary L. Bradshaw & Jan M. Zytkow - 1993 - In Alvin I. Goldman (ed.), Readings in Philosophy and Cognitive Science. Cambridge: MIT Press.
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  • Laboratory Replication of Scientific Discovery Processes.Yulin Qin & Herbert A. Simon - 1990 - Cognitive Science 14 (2):281-312.
    Fourteen subjects were tape‐recorded while they undertook to find a law to summarize numerical data they were given. The source of the data was not identified, nor were the variables labeled semantically. Unknown to the subjects, the data were measurements of the distances of the planets from the sun and the periods of their revolutions about it—equivalent to the data used by Johannes Kepler to discover his third law of planetary motion.Four of the 14 subjects discovered the same law as (...)
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  • EPAM‐like Models of Recognition and Learning.Edward A. Feigenbaum & Herbert A. Simon - 1984 - Cognitive Science 8 (4):305-336.
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  • Eurisko: A program that learns new heuristics and domain concepts.Douglas B. Lenat - 1983 - Artificial Intelligence 21 (1-2):61-98.
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  • Simulation of expert memory using EPAM IV.Howard B. Richman, James J. Staszewski & Herbert A. Simon - 1995 - Psychological Review 102 (2):305-330.
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  • Causality and model abstraction.Yumi Iwasaki & Herbert A. Simon - 1994 - Artificial Intelligence 67 (1):143-194.
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  • Review: The Grand Leap; Reviewed Work: Causation, Prediction, and Search. [REVIEW]Peter Spirtes, Clark Glymour & Richard Scheines - 1996 - British Journal for the Philosophy of Science 47 (1):113-123.
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  • The axiomatization of physical theories.Herbert A. Simon - 1970 - Philosophy of Science 37 (1):16-26.
    The task of axiomatizing physical theories has attracted, in recent years, some interest among both empirical scientists and logicians. However, the axiomatizations produced by either one of these two groups seldom appear satisfactory to the members of the other. It is the purpose of this paper to develop an approach that will satisfy the criteria of both, hence permit us to construct axiomatizations that will meet simultaneously the standards and needs of logicians and of empirical scientists.
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  • The nature of heuristics.Douglas B. Lenat - 1982 - Artificial Intelligence 19 (2):189-249.
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  • Ramsey eliminability and the testability of scientific theories.Herbert A. Simon & Guy J. Groen - 1973 - British Journal for the Philosophy of Science 24 (4):367-380.
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  • Toward a model of representation changes.Richard E. Korf - 1980 - Artificial Intelligence 14 (1):41-78.
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  • Dictionary of the History of Science.W. F. Bynum, E. J. Browne & Roy Porter - 1983 - Journal of the History of Biology 16 (1):178-179.
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  • Functional transformations in AI discovery systems.Wei-Min Shen - 1990 - Artificial Intelligence 41 (3):257-272.
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  • Fitness requirements for scientific theories.Herbert A. Simon - 1983 - British Journal for the Philosophy of Science 34 (4):355-365.
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  • Fitness requirements for scientific theories containing recursive theoretical terms.Wei-min Shen & Herbert A. Simon - 1993 - British Journal for the Philosophy of Science 44 (4):641-652.
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