Using attention in belief revision

Authors:
Xueming Huang;Gordon I. McCalla;Eric Neufeld
Affiliations:
ARIES Laboratory, Department of Computational Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada;ARIES Laboratory, Department of Computational Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada;ARIES Laboratory, Department of Computational Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Venue:
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
Year:
1991

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Abstract

Belief revision for an intelligent system is usually computationally expensive. Here we tackle this problem by using focus in belief revision: that is, revision occurs only in a subset of beliefs under attention (or in focus). Attention can be shifted within the belief base, thus allowing use and revision of other subsets of beliefs. This attention-shifting belief revision architecture shows promise to allow efficient and natural revision of belief bases.