A compilation based approach to conformant probabilistic planning with stochastic actions Academic Article uri icon


  • 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,...

publication date

  • January 1, 2015