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  1. Complexity results for explanations in the structural-model approach.Thomas Eiter & Thomas Lukasiewicz - 2004 - Artificial Intelligence 154 (1-2):145-198.
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  • Functional completion.Vladimir Lifschitz & Fangkai Yang - 2013 - Journal of Applied Non-Classical Logics 23 (1-2):121-130.
    Nonmonotonic causal logic is a knowledge representation language designed for describing domains that involve actions and change. The process of literal completion, similar to program completion familiar from the theory of logic programming, can be used to translate some nonmonotonic causal theories into classical logic. Its applicability is restricted, however, to theories that deal with truth-valued fluents, represented by predicate symbols. In this note we introduce functional completion—a more general process that can be applied to causal theories in which fluents (...)
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  • Loop formulas for circumscription.Joohyung Lee & Fangzhen Lin - 2006 - Artificial Intelligence 170 (2):160-185.
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  • Causality, Modality, and Explanation.Graham White - 2008 - Notre Dame Journal of Formal Logic 49 (3):313-343.
    We start with Fodor's critique of cognitive science in "The mind doesn't work that way: The scope and limits of computational psychology": he argues that much mental activity cannot be handled by the current methods of cognitive science because it is nonmonotonic and, therefore, is global in nature, is not context-free, and is thus not capable of being formalized by a Turing-like mental architecture. We look at the use of nonmonotonic logic in the artificial intelligence community, particularly with the discussion (...)
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  • The semantics of variables in action descriptions.Vladimir Lifschitz & W. Ren - manuscript
    structures, or interpretations, in the sense of first-order logic. In C+, on the other hand, a state is an interpreta-.
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  • Causes and explanations in the structural-model approach: Tractable cases.Thomas Eiter & Thomas Lukasiewicz - 2006 - Artificial Intelligence 170 (6-7):542-580.
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  • First-order stable model semantics with intensional functions.Michael Bartholomew & Joohyung Lee - 2019 - Artificial Intelligence 273 (C):56-93.
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  • Characterizing causal action theories and their implementations in answer set programming.Haodi Zhang & Fangzhen Lin - 2017 - Artificial Intelligence 248 (C):1-8.
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  • Approximation of action theories and its application to conformant planning.Phan Huy Tu, Tran Cao Son, Michael Gelfond & A. Ricardo Morales - 2011 - Artificial Intelligence 175 (1):79-119.
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  • Twenty-five years of linguistics and philosophy.Francis Jeffry Pelletier & Richmond H. Thomason - 2002 - Linguistics and Philosophy 25 (5-6):507-529.
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  • SAT-based planning in complex domains: Concurrency, constraints and nondeterminism.Claudio Castellini, Enrico Giunchiglia & Armando Tacchella - 2003 - Artificial Intelligence 147 (1-2):85-117.
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  • A causal approach to nonmonotonic reasoning.Alexander Bochman - 2004 - Artificial Intelligence 160 (1-2):105-143.
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