Heuristic guidance measures for conformant planning

Daniel Bryce, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

Scaling conformant planning is a problem that has received much attention of late. Many planners solve the problem as a search in the space of belief states, and some heuristic guidance techniques have been developed to estimate the distance between belief states. We claim that heuristic techniques in the past involved an ad hoc combination of classical planning heuristics and cardinality measures. We discuss how to derive heuristics systematically, with the help of planning graphs, such that the measures reflect the reachability of relevant states within belief states. To demonstrate these ideas we show how distances between belief states can be estimated by a set of reachability heuristics. We empirically evaluate their effectiveness within a conformant regression planner named C Alt Alt.

Original languageEnglish (US)
Title of host publicationProceedings of the 14th International Conference on Automated Planning and Scheduling, ICAPS 2004
EditorsS. Zilberstein, J. Koehler, S. Koenig
Pages365-374
Number of pages10
StatePublished - Dec 1 2004
EventProceedings of the 14th International Conference on Automated Planning and Scheduling, ICAPS 2004 - Whistler, BC, Canada
Duration: Jun 3 2004Jun 7 2004

Publication series

NameProceedings of the 14th International Conference on Automated Planning and Scheduling, ICAPS 2004

Other

OtherProceedings of the 14th International Conference on Automated Planning and Scheduling, ICAPS 2004
CountryCanada
CityWhistler, BC
Period6/3/046/7/04

ASJC Scopus subject areas

  • Engineering(all)

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    Bryce, D., & Kambhampati, S. (2004). Heuristic guidance measures for conformant planning. In S. Zilberstein, J. Koehler, & S. Koenig (Eds.), Proceedings of the 14th International Conference on Automated Planning and Scheduling, ICAPS 2004 (pp. 365-374). (Proceedings of the 14th International Conference on Automated Planning and Scheduling, ICAPS 2004).