A multi-path compilation approach to contingent planning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

We describe a new sound and complete method for compiling contingent planning problems with sensing actions into classical planning. Our method encodes conditional plans within a linear, classical plan. This allows our planner, MPSR, to reason about multiple future outcomes of sensing actions, and makes it less susceptible to dead-ends. MPRS, however, generates very large classical planning problems. To overcome this, we use an incomplete variant of the method, based on state sampling, within an online replanner. On most current domains, MPSR finds plans faster, although its plans are often longer. But on a new challenging variant of Wumpus with dead-ends, it finds smaller plans, faster, and scales better.

Original languageEnglish
Title of host publicationAAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference
Pages1868-1874
Number of pages7
StatePublished - 7 Nov 2012
Event26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12 - Toronto, ON, Canada
Duration: 22 Jul 201226 Jul 2012

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume3

Conference

Conference26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12
Country/TerritoryCanada
CityToronto, ON
Period22/07/1226/07/12

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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