2018/10/22 by Damien Pellier, Pellier, Damien, Bruno Bouzy +3
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #FOS: Computer and information sciences #Robotic Path Planning Algorithms
paper · pdf · doi:10.48550/arxiv.1810.09150
openalex publication_date 2018/10/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.