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A mean-based approach for real-time planning

In this paper, we introduce a new heuristic search algorithm based on mean values for real-time 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 a real-time planner in the context of classical planning. Compared to UCT, at leaf nodes, MHSP replaces the simulations by heuristic values given by planning graph techniques. When the heuristic is admissible, the initial mean values of nodes are optimistic, which is a correct way of guiding exploration.