A Multi-Path Compilation Approach to Contingent Planning

Research output: Contribution to conferencePaperpeer-review

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 languageAmerican English
Pages1868-1874
Number of pages7
StatePublished - 1 Jan 2012
Event26th AAAI Conference on Artificial Intelligence, AAAI 2012 - Toronto, Canada
Duration: 22 Jul 201226 Jul 2012

Conference

Conference26th AAAI Conference on Artificial Intelligence, AAAI 2012
Country/TerritoryCanada
CityToronto
Period22/07/1226/07/12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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