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  1. Making believers out of computers.Hector J. Levesque - 1986 - Artificial Intelligence 30 (1):81-108.
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  • Quantifying inductive bias: AI learning algorithms and Valiant's learning framework.David Haussler - 1988 - Artificial Intelligence 36 (2):177-221.
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  • Theory refinement combining analytical and empirical methods.Dirk Ourston & Raymond J. Mooney - 1994 - Artificial Intelligence 66 (2):273-309.
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  • SOAR: An architecture for general intelligence.John E. Laird, Allen Newell & Paul S. Rosenbloom - 1987 - Artificial Intelligence 33 (1):1-64.
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  • Two theses of knowledge representation: Language restrictions, taxonomic classification, and the utility of representation services.Jon Doyle & Ramesh S. Patil - 1991 - Artificial Intelligence 48 (3):261-297.
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  • Connectionist learning procedures.Geoffrey E. Hinton - 1989 - Artificial Intelligence 40 (1-3):185-234.
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  • Classifier systems and genetic algorithms.L. B. Booker, D. E. Goldberg & J. H. Holland - 1989 - Artificial Intelligence 40 (1-3):235-282.
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  • Explanation-based learning:A problem solving perspective.Steven Minton, Jaime G. Carbonell, Craig A. Knoblock, Daniel R. Kuokka, Oren Etzioni & Yolanda Gil - 1989 - Artificial Intelligence 40 (1-3):63-118.
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  • The complexity of theory revision.Russell Greiner - 1999 - Artificial Intelligence 107 (2):175-217.
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  • Optimal problem-solving search: All-or-none solutions.Herbert A. Simon & Joseph B. Kadane - 1975 - Artificial Intelligence 6 (3):235-247.
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  • Default reasoning in semantic networks: A formalization of recognition and inheritance.Lokendra Shastri - 1989 - Artificial Intelligence 39 (3):283-355.
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  • Controlling backward inference.David E. Smith - 1989 - Artificial Intelligence 39 (2):145-208.
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  • Finding optimal derivation strategies in redundant knowledge bases.Russell Greiner - 1991 - Artificial Intelligence 50 (1):95-115.
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  • Probably approximately optimal satisficing strategies.Russell Greiner & Pekka Orponen - 1996 - Artificial Intelligence 82 (1-2):21-44.
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