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  1. Practical reasoning for very expressive description logics.I. Horrocks, U. Sattler & S. Tobies - 2000 - Logic Journal of the IGPL 8 (3):239-263.
    Description Logics are a family of knowledge representation formalisms mainly characterised by constructors to build complex concepts and roles from atomic ones. Expressive role constructors are important in many applications, but can be computationally problematical.We present an algorithm that decides satisfiability of the DL ALC extended with transitive and inverse roles and functional restrictions with respect to general concept inclusion axioms and role hierarchies; early experiments indicate that this algorithm is well-suited for implementation. Additionally, we show that ALC extended with (...)
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  • The complexity of existential quantification in concept languages.Francesco M. Donini, Maurizio Lenzerini, Daniele Nardi, Bernhard Hollunder, Werner Nutt & Alberto Marchetti Spaccamela - 1992 - Artificial Intelligence 53 (2-3):309-327.
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  • An overview of tableau algorithms for description logics.Franz Baader & Ulrike Sattler - 2001 - Studia Logica 69 (1):5-40.
    Description logics are a family of knowledge representation formalisms that are descended from semantic networks and frames via the system Kl-one. During the last decade, it has been shown that the important reasoning problems (like subsumption and satisfiability) in a great variety of description logics can be decided using tableau-like algorithms. This is not very surprising since description logics have turned out to be closely related to propositional modal logics and logics of programs (such as propositional dynamic logic), for which (...)
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  • Attributive concept descriptions with complements.Manfred Schmidt-Schauß & Gert Smolka - 1991 - Artificial Intelligence 48 (1):1-26.
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  • Terminological reasoning is inherently intractable.Bernhard Nebel - 1990 - Artificial Intelligence 43 (2):235-249.
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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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