Parallelizing State Space Plans Online

Romeo Sanchez Nigenda, Subbarao Kambhampati

Abstract: Searching for parallel solutions in state space planners is a challenging problem, because it would require the planners to branch on all possible subsets of parallel actions, exponentially increasing their branching factor. We introduce a variant of our heuristic state search planner AltAlt, which generates parallel plans by using greedy online parallelization of partial plans. Empirical results show that our online approach outperforms post-processing (offline) techniques in terms of the quality of the solutions returned.