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Efficient Reasoning Using the Local Closed-World Assumption

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2000)

Abstract

We present a sound and complete, tractable inference method for reasoning with localized closed world assumptions (LCWA’s) which can be used in applications where a reasoning or planning agent can not assume complete information about planning or reasoning states. This Open World Assumption is generally necessary in most realistic robotics applications. The inference procedure subsumes that described in Etzioni et al [9], and others. In addition, it provides a great deal more expressivity, permitting limited use of negation and disjunction in the representation of LCWA’s, while still retaining tractability. The ap- proach is based on the use of circumscription and quantifier elimination techniques and inference is viewed as querying a deductive database. Both the preprocessing of the database using circumscription and quan- tifier elimination, and the inference method itself, have polynomial time and space complexity.

The authors are supported in part by a basic research grant from the Wallenberg Foundation, Sweden.

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Doherty, P., Lukaszewicz, W., Szalas, A. (2000). Efficient Reasoning Using the Local Closed-World Assumption. In: Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2000. Lecture Notes in Computer Science, vol 1904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45331-8_5

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  • DOI: https://doi.org/10.1007/3-540-45331-8_5

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  • Print ISBN: 978-3-540-41044-7

  • Online ISBN: 978-3-540-45331-4

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