寻路
计算机科学
启发式
路径(计算)
系列(地层学)
计算
数学优化
空格(标点符号)
最短路径问题
算法
人工智能
理论计算机科学
图形
数学
操作系统
生物
古生物学
程序设计语言
标识
DOI:10.1609/aiide.v1i1.18726
摘要
Cooperative Pathfinding is a multi-agent path planning problem where agents must find non-colliding routes to separate destinations, given full information about the routes of other agents. This paper presents three new algorithms for efficiently solving this problem, suitable for use in Real-Time Strategy games and other real-time environments. The algorithms are decoupled approaches that break down the problem into a series of single-agent searches. Cooperative A* (CA*) searches space-time for a non-colliding route. Hierarchical Cooperative A* (HCA*) uses an abstract heuristic to boost performance. Finally, Windowed Hierarchical Cooperative A* (WHCA*) limits the space-time search depth to a dynamic window, spreading computation over the duration of the route. The algorithms are applied to a series of challenging, maze-like environments, and compared to A* with Local Repair (the current video-games industry standard). The results show that the new algorithms, especially WHCA*, are robust and efficient solutions to the Cooperative Pathfinding problem, finding more successful routes and following better paths than Local Repair A*
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