Property persistence in the situation calculus

Authors:
Ryan F. Kelly;Adrian R. Pearce
Affiliations:
NICTA Victoria Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Victoria, Australia;NICTA Victoria Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Victoria, Australia
Venue:
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Year:
2007

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Abstract

We develop an algorithm for reducing universally quantified situation calculus queries to a form more amenable to automated reasoning. Universal quantification in the situation calculus requires a second-order induction axiom, making automated reasoning difficult for such queries. We show how to reduce queries about property persistence, a common family of universally-quantified query, to an equivalent form that does not quantify over situations. The algorithm for doing so utilizes only first-order reasoning. We give several examples of important reasoning tasks that are facilitated by our approach, including checking for goal impossibility and reasoning about knowledge with partial observability of actions.