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  1. Abstraction for non-ground answer set programs.Zeynep G. Saribatur, Thomas Eiter & Peter Schüller - 2021 - Artificial Intelligence 300 (C):103563.
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  • Speeding up inferences using relevance reasoning: a formalism and algorithms.Alon Y. Levy, Richard E. Fikes & Yehoshua Sagiv - 1997 - Artificial Intelligence 97 (1-2):83-136.
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  • Proving theorems by reuse.Christoph Walther & Thomas Kolbe - 2000 - Artificial Intelligence 116 (1-2):17-66.
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  • Downward refinement and the efficiency of hierarchical problem solving.Fahiem Bacchus & Qiang Yang - 1994 - Artificial Intelligence 71 (1):43-100.
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  • A goal-dependent abstraction for legal reasoning by analogy.Tokuyasu Kakuta, Makoto Haraguchi & Yoshiaki Okubo - 1997 - Artificial Intelligence and Law 5 (1-2):97-118.
    This paper presents a new algorithm to find an appropriate similarityunder which we apply legal rules analogically. Since there may exist a lotof similarities between the premises of rule and a case in inquiry, we haveto select an appropriate similarity that is relevant to both thelegal rule and a top goal of our legal reasoning. For this purpose, a newcriterion to distinguish the appropriate similarities from the others isproposed and tested. The criterion is based on Goal-DependentAbstraction (GDA) to select a (...)
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  • Man-machine theorem proving in graph theory.Dragoš Cvetković & Irena Pevac - 1988 - Artificial Intelligence 35 (1):1-23.
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  • Reasoning about model accuracy.Daniel S. Weld - 1992 - Artificial Intelligence 56 (2-3):255-300.
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  • Introduction to the Special Volume on Reformulation.Thomas Ellman & Fausto Giunchiglia - 2005 - Artificial Intelligence 162 (1-2):3-5.
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  • A theory of abstraction.Fausto Giunchiglia & Toby Walsh - 1992 - Artificial Intelligence 57 (2-3):323-389.
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  • A relevance restriction strategy for automated deduction.David A. Plaisted & Adnan Yahya - 2003 - Artificial Intelligence 144 (1-2):59-93.
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  • Automatically generating abstractions for planning.Craig A. Knoblock - 1994 - Artificial Intelligence 68 (2):243-302.
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  • A simplified problem reduction format.David A. Plaisted - 1982 - Artificial Intelligence 18 (2):227-261.
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  • Towards a practical theory of reformulation for reasoning about physical systems.Berthe Y. Choueiry, Yumi Iwasaki & Sheila McIlraith - 2005 - Artificial Intelligence 162 (1-2):145-204.
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