Craig Boutilier
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: cebly@cs.toronto.edu
Abstract
Monitoring plan preconditions can allow for replanning when a precondition
fails, generally far in advance of the point in the plan where the
precondition is relevant. However, monitoring is generally costly, and
some precondition failures have a very small impact on plan quality. We
formulate a model for optimal precondition monitoring, using
partially-observable Markov decisions processes, and describe methods for
solving this model effectively, though approximately. Specifically, we
show that the single-precondition monitoring problem is generally
tractable, and the multiple-precondition monitoring policies can be
effectively approximated using single-precondition solutions.
To appear, UAI-2000
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