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A Mean-based Approach for Real-Time Planning

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 clas- sical planning. MHSP is evaluated on di erent 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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https://hal.inria.fr/hal-00975972
Contributor : Damien Pellier <>
Submitted on : Wednesday, April 9, 2014 - 2:02:35 PM
Last modification on : Friday, April 10, 2020 - 5:29:32 PM
Long-term archiving on: : Monday, April 10, 2017 - 11:34:42 AM

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  • HAL Id : hal-00975972, version 1

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Damien Pellier, Bruno Bouzy, Marc Métivier. A Mean-based Approach for Real-Time Planning. International Conference on Autonomous Agents and Multiagent Systems, May 2010, Toronto, Canada. ⟨hal-00975972⟩

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