An UCT Approach for Anytime Agent-Based Planning

In this paper, we introduce a new heuristic search algorithm based on mean values for anytime planning, called MHSP. It consists in associating the principles of UCT, a bandit-based algorithm which gave very good results in computer games, and especially in Computer Go, with heuristic search in order to obtain an anytime planner that provides partial plans before finding a solution plan, and furthermore finding an optimal plan. The algorithm is evaluated in different classical planning problems and compared to some major planning algorithms. Finally, our results highlight the capacity of MHSP to return partial plans which tend to an optimal plan over the time.

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