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  1. Downward refinement and the efficiency of hierarchical problem solving.Fahiem Bacchus & Qiang Yang - 1994 - Artificial Intelligence 71 (1):43-100.
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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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  • 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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  • 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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  • Domain-independent planning Representation and plan generation.David E. Wilkins - 1984 - Artificial Intelligence 22 (3):269-301.
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  • Planning with constraints.Mark Stefik - 1981 - Artificial Intelligence 16 (2):111-139.
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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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  • Theorem proving with abstraction.David A. Plaisted - 1981 - Artificial Intelligence 16 (1):47-108.
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  • Quantitative results concerning the utility of explanation-based learning.Steven Minton - 1990 - Artificial Intelligence 42 (2-3):363-391.
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  • Planning as search: A quantitative approach.Richard E. Korf - 1987 - Artificial Intelligence 33 (1):65-88.
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  • Macro-operators: A weak method for learning.Richard E. Korf - 1985 - Artificial Intelligence 26 (1):35-77.
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  • Learning problem solving strategies using refinement and macro generation.H. Altay Güvenir & George W. Ernst - 1990 - Artificial Intelligence 44 (1-2):209-243.
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  • A theory of abstraction.Fausto Giunchiglia & Toby Walsh - 1992 - Artificial Intelligence 57 (2-3):323-389.
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  • Learning and executing generalized robot plans.Richard E. Fikes, Peter E. Hart & Nils J. Nilsson - 1972 - Artificial Intelligence 3 (C):251-288.
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  • A structural theory of explanation-based learning.Oren Etzioni - 1993 - Artificial Intelligence 60 (1):93-139.
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