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  1. Transcending inductive category formation in learning.Roger C. Schank, Gregg C. Collins & Lawrence E. Hunter - 1986 - Behavioral and Brain Sciences 9 (4):639-651.
    The inductive category formation framework, an influential set of theories of learning in psychology and artificial intelligence, is deeply flawed. In this framework a set of necessary and sufficient features is taken to define a category. Such definitions are not functionally justified, are not used by people, and are not inducible by a learning system. Inductive theories depend on having access to all and only relevant features, which is not only impossible but begs a key question in learning. The crucial (...)
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  • Strips: A new approach to the application of theorem proving to problem solving.Richard E. Fikes & Nils J. Nilsson - 1971 - Artificial Intelligence 2 (3-4):189-208.
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  • Planning in a hierarchy of abstraction spaces.Earl D. Sacerdoti - 1974 - Artificial Intelligence 5 (2):115-135.
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  • Selection of most representative training examples and incremental generation of VL₁ hypotheses: the underlying methodology and the description of programs, ESEL and AQ11.Ryszard Stanisław Michalski - 1978 - Urbana: Dept. of Computer Science, University of Illinois at Urbana-Champaign. Edited by James Larson.
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