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Reasoning with models

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Artificial Intelligence 87 (1-2):187-213 (1996)

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  1. First order LUB approximations: characterization and algorithms.Alvaro del Val - 2005 - Artificial Intelligence 162 (1-2):7-48.
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  • Semantical and computational aspects of Horn approximations.Marco Cadoli & Francesco Scarcello - 2000 - Artificial Intelligence 119 (1-2):1-17.
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  • Is intractability of nonmonotonic reasoning a real drawback?Marco Cadoli, Francesco M. Donini & Marco Schaerf - 1996 - Artificial Intelligence 88 (1-2):215-251.
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  • Support set selection for a bductive and default reasoning.Bart Selman & Hector J. Levesque - 1996 - Artificial Intelligence 82 (1-2):259-272.
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  • On the hardness of approximate reasoning.Dan Roth - 1996 - Artificial Intelligence 82 (1-2):273-302.
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  • What makes propositional abduction tractable.Gustav Nordh & Bruno Zanuttini - 2008 - Artificial Intelligence 172 (10):1245-1284.
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  • Defaults and relevance in model-based reasoning.Roni Khardon & Dan Roth - 1997 - Artificial Intelligence 97 (1-2):169-193.
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  • Horn approximations of empirical data.Henry Kautz, Michael Kearns & Bart Selman - 1995 - Artificial Intelligence 74 (1):129-145.
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  • On functional dependencies in q-Horn theories.Toshihide Ibaraki, Alexander Kogan & Kazuhisa Makino - 2001 - Artificial Intelligence 131 (1-2):171-187.
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  • Ordered binary decision diagrams as knowledge-bases.Takashi Horiyama & Toshihide Ibaraki - 2002 - Artificial Intelligence 136 (2):189-213.
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  • The complexity of reasoning with FODD and GFODD.Benjamin J. Hescott & Roni Khardon - 2015 - Artificial Intelligence 229 (C):1-32.
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  • The complexity of theory revision.Russell Greiner - 1999 - Artificial Intelligence 107 (2):175-217.
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