Mean-based Heuristic Search 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 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.
Keywords
Cite
@article{arxiv.1810.09150,
title = {Mean-based Heuristic Search for Real-Time Planning},
author = {Damien Pellier and Bruno Bouzy and Marc Métivier},
journal= {arXiv preprint arXiv:1810.09150},
year = {2018}
}
Comments
Journ\'ees Francophones de Planification, D\'ecision, Apprentissage pour la conduite de syst\`emes, 2010