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  1. Succinctness as a source of complexity in logical formalisms.Georg Gottlob, Nicola Leone & Helmut Veith - 1999 - Annals of Pure and Applied Logic 97 (1-3):231-260.
    The often observed complexity gap between the expressiveness of a logical formalism and its exponentially harder expression complexity is proven for all logical formalisms which satisfy natural closure conditions. The expression complexity of the prefix classes of second-order logic can thus be located in the corresponding classes of the weak exponential hierarchies; further results about expression complexity in database theory, logic programming, nonmonotonic reasoning, first-order logic with Henkin quantifiers and default logic are concluded. The proof method illustrates the significance of (...)
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  • Circumscription — A Form of Non-Monotonic Reasoning.John McCarthy - 1980 - Artificial Intelligence 13 (1-2):27–39.
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  • A Framework for Representing Knowledge.Marvin Minsky - unknown
    It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities.
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  • Semantic Considerations on nonmonotonic Logic.Robert C. Moore - 1985 - Artificial Intelligence 25 (1):75-94.
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  • A logic for default reasoning.Ray Reiter - 1980 - Artificial Intelligence 13 (1-2):81-137.
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  • Extending and implementing the stable model semantics.Patrik Simons, Ilkka Niemelä & Timo Soininen - 2002 - Artificial Intelligence 138 (1-2):181-234.
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  • Non-monotonic logic I.Drew McDermott & Jon Doyle - 1980 - Artificial Intelligence 13 (1-2):41-72.
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  • (1 other version)Some Philosophical Problems from the Standpoint of Artificial Intelligence.J. McCarthy & P. J. Hayes - 1969 - Machine Intelligence 4:463-502.
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  • ASSAT: computing answer sets of a logic program by SAT solvers.Fangzhen Lin & Yuting Zhao - 2004 - Artificial Intelligence 157 (1-2):115-137.
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  • Applications of Circumscription to Formalizing Common Sense Knowledge.John McCarthy - 1986 - Artificial Intelligence 28 (1):89–116.
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