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arXiv · 1810.09150

Mean-based Heuristic Search for Real-Time Planning

Damien Pellier·Bruno Bouzy·Marc Métivier
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Abstract

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. MHSP is evaluated on different planning problems and compared to existing algorithms performing on-line search and learning. Besides, our results highlight the capacity of MHSP to return plans in a real-time manner which tend to an optimal plan over the time which is faster and of better quality compared to existing algorithms in the literature.

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Damien Pellier, Bruno Bouzy, Marc Métivier. 2018-10-22. Mean-based Heuristic Search for Real-Time Planning. https://arxiv.org/abs/1810.09150

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