Probabilistic Temporal Planning with Uncertain Durations

Few temporal planners handle both concurrency and uncertain durations, but these features commonly co-occur in realworld domains. In this paper, we discuss the challenges caused by concurrent, durative actions whose durations are uncertain. We present five implemented algorithms, including ∆DURprun, a planner guaranteed to find the optimal policy. An empirical comparison reveals that ∆DURexp, our fastest planner, obtains orders of magnitude speed-up compared to ∆DURprun— with little loss in solution quality. Importantly, our algorithms can handle probabilistic effects in addition to stochastic durations, and they are effective even when duration distributions are multi-modal.