A compilation based approach to conformant probabilistic planning with stochastic actions

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Abstract

We extend RBPP, the state-of-the-art, translation-based planner for conformant probabilistic planning (CPP) with deterministic actions, to handle a wide set of CPPs with stochastic actions. Our planner uses relevance analysis to divide a probabilistic "failure-allowance" between the initial state and the stochastic actions. Using its "initial-state allowance," it uses relevance analysis to select a subset of the set of initial states on which planning efforts will focus. Then, it generates a deterministic planning problem using all-outcome determinization in which action cost reflects the probability of the modeled outcome. Finally, a cost-bounded classical planner generates a plan with failure probability lower than the "stochastic-effect allowance." Our compilation method is sound, but incomplete, as it may underestimates the success probability of a plan. Yet, it scales up much better than the state-of-the-art PFF planner, solving larger problems and handling tighter probabilistic bounds on existing benchmarks.

Original languageEnglish
Title of host publicationICAPS 2015 - Proceedings of the 25th International Conference on Automated Planning and Scheduling
EditorsPatrik Haslum, Carmel Domshlak, Ronen Brafman, Shlomo Zilberstein
PublisherAAAI press
Pages220-224
Number of pages5
ISBN (Electronic)9781577357315
StatePublished - 1 Jan 2015
Event25th International Conference on Automated Planning and Scheduling, ICAPS 2015 - Jerusalem, Israel
Duration: 7 Jun 201511 Jun 2015

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2015-January
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference25th International Conference on Automated Planning and Scheduling, ICAPS 2015
Country/TerritoryIsrael
CityJerusalem
Period7/06/1511/06/15

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