English

Approximately Optimal Monitoring of Plan Preconditions

Artificial Intelligence 2013-01-18 v1

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 efficitively, though approximately. Specifically, we show that the single-precondition monitoring problem is generally tractable, and the multiple-precondition monitoring policies can be efficitively approximated using single-precondition soultions.

Keywords

Cite

@article{arxiv.1301.3839,
  title  = {Approximately Optimal Monitoring of Plan Preconditions},
  author = {Craig Boutilier},
  journal= {arXiv preprint arXiv:1301.3839},
  year   = {2013}
}

Comments

Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)