A Compilation Based Approach to Conformant Probabilistic Planning with Stochastic Actions

Authors

  • Ran Taig Ben Gurion University of the Negev, Beer-Sheva, Israel
  • Ronen Brafman Ben Gurion University of the Negev, Beer-Sheva, Israel

DOI:

https://doi.org/10.1609/icaps.v25i1.13718

Keywords:

Conformant Probabilistic Planning, Translation Based Approach

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 modeledoutcome. 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.

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Published

2015-04-08

How to Cite

Taig, R., & Brafman, R. (2015). A Compilation Based Approach to Conformant Probabilistic Planning with Stochastic Actions. Proceedings of the International Conference on Automated Planning and Scheduling, 25(1), 220-224. https://doi.org/10.1609/icaps.v25i1.13718