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Marco Cadoli [9]M. Cadoli [1]
  1.  7
    Tractable reasoning via approximation.Marco Schaerf & Marco Cadoli - 1995 - Artificial Intelligence 74 (2):249-310.
  2.  2
    The size of a revised knowledge base.Marco Cadoli, Francesco M. Donini, Paolo Liberatore & Marco Schaerf - 1999 - Artificial Intelligence 115 (1):25-64.
  3.  5
    Semantical and computational aspects of Horn approximations.Marco Cadoli & Francesco Scarcello - 2000 - Artificial Intelligence 119 (1-2):1-17.
  4.  7
    Is intractability of nonmonotonic reasoning a real drawback?Marco Cadoli, Francesco M. Donini & Marco Schaerf - 1996 - Artificial Intelligence 88 (1-2):215-251.
  5.  5
    An efficient method for eliminating varying predicates from a circumscription.Marco Cadoli, Thomas Eiter & Georg Gottlob - 1992 - Artificial Intelligence 54 (3):397-410.
  6.  2
    Compiling problem specifications into SAT.Marco Cadoli & Andrea Schaerf - 2005 - Artificial Intelligence 162 (1-2):89-120.
  7. Index of Authors of Volume 7.V. M. Abrusci, G. Attardi, D. Basin, R. Booth, T. Borghuis, S. Buvac, M. Cadoli, J. Cantwell, H. de Nivelle & M. Dymetman - 1998 - Journal of Logic, Language, and Information 7 (507):507.
     
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  8.  4
    Automated reformulation of specifications by safe delay of constraints.Marco Cadoli & Toni Mancini - 2006 - Artificial Intelligence 170 (8-9):779-801.
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  9.  1
    Exploiting functional dependencies in declarative problem specifications.Toni Mancini & Marco Cadoli - 2007 - Artificial Intelligence 171 (16-17):985-1010.
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  10.  44
    Using abstract resources to control reasoning.Richard W. Weyhrauch, Marco Cadoli & Carolyn L. Talcott - 1998 - Journal of Logic, Language and Information 7 (1):77-101.
    Many formalisms for reasoning about knowing commit an agent to be logically omniscient. Logical omniscience is an unrealistic principle for us to use to build a real-world agent, since it commits the agent to knowing infinitely many things. A number of formalizations of knowledge have been developed that do not ascribe logical omniscience to agents. With few exceptions, these approaches are modifications of the possible-worlds semantics. In this paper we use a combination of several general techniques for building non-omniscient reasoners. (...)
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