LiU Electronic Press
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Author:
Doherty, Patrick (Linköping University, The Institute of Technology) (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab)
Lukaszewicz, Witold (Linköping University, The Institute of Technology) (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab)
Szalas, Andrzej (Linköping University, The Institute of Technology) (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab)
Title:
Efficient reasoning using the local closed-world assumption
Department:
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab
Linköping University, The Institute of Technology
Publication type:
Conference paper (Refereed)
Language:
English
In:
Proceedings of the 9th International Conference on Artificial Intelligence: Methodology, Systems and Applications (AIMSA)
Publisher: Springer
Series:
Lecture Notes in Computer Science, ISSN 0302-9743; 1904
Pages:
49-58
Year of publ.:
2000
URI:
urn:nbn:se:liu:diva-41590
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-41590
ISBN:
3-540-41044-9
Local ID:
58057
Subject category:
Computer Science
SVEP category:
Computer science
Abstract(en) :

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.

Available from:
2009-10-10
Created:
2009-10-10
Last updated:
2011-03-21
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17 hits