Fault Tolerant Planning: Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning

Rune Møller Jensen, Manuela M. Veloso, Randal E. Bryant

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Symbolic non-deterministic planning represents action effects as sets of possible next states. In this paper, we move toward a more probabilistic uncertainty model by distinguishing between likely primary effects and unlikely secondary effects of actions. We consider the practically important case where secondary effects are failures, and introduce n-fault tolerant plans that are robust for up to n faults occurring during plan execution. Fault tolerant plans are more restrictive than weak plans, but more relaxed than strong cyclic and strong plans. We show that optimal n-fault tolerant plans can be generated by the usual strong algorithm. However, due to non-local error states, it is often beneficial to decouple the planning for primary and secondary effects. We employ this approach for two specialized algorithms 1-FTP (blind) and 1-GFTP (guided) and demonstrate their advantages experimentally in significant real-world domains.
Original languageEnglish
Title of host publicationProceedings of the Fourteenth International Conference on Automated Planning and Scheduling (ICAPS-04)
Number of pages10
PublisherAAAI Press
Publication date2004
Pages335-344
ISBN (Print)9781577352006
Publication statusPublished - 2004

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