Multiagent Path Finding With Persistence Conflicts

Bikramjit Banerjee, Caleb E. Davis
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引用次数: 6

Abstract

Multiagent path finding is the problem of finding paths for a set of agents—one for each agent—in a graph that the agents navigate simultaneously. Agents must navigate from their individual start to goal vertices without any collision. We argue that the prevalent treatment of path conflicts in the literature is incomplete for applications, such as computer games and crowd simulations, and extend the definition of path conflicts to accommodate cases where agents persist in their intermediate locations and even after reaching their goals. We show that an existing algorithm, conflict-based search (CBS), can be extended to handle these cases while preserving its optimality. Experiments show that our variant of CBS generates fewer nodes and runs faster than a competing algorithm.
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具有持久性冲突的多智能体寻径
多代理寻径问题是在代理同时导航的图中为一组代理(每个代理一个)寻找路径。智能体必须从它们各自的起始点导航到目标点而不发生任何碰撞。我们认为,文献中对路径冲突的普遍处理对于计算机游戏和人群模拟等应用来说是不完整的,并扩展了路径冲突的定义,以适应智能体坚持在中间位置甚至达到目标后的情况。我们证明了现有的基于冲突的搜索(CBS)算法可以扩展到处理这些情况,同时保持其最优性。实验表明,我们的CBS变体比竞争算法生成的节点更少,运行速度更快。
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来源期刊
IEEE Transactions on Computational Intelligence and AI in Games
IEEE Transactions on Computational Intelligence and AI in Games COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
4.60
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Cessation. The IEEE Transactions on Computational Intelligence and AI in Games (T-CIAIG) publishes archival journal quality original papers in computational intelligence and related areas in artificial intelligence applied to games, including but not limited to videogames, mathematical games, human–computer interactions in games, and games involving physical objects. Emphasis is placed on the use of these methods to improve performance in and understanding of the dynamics of games, as well as gaining insight into the properties of the methods as applied to games. It also includes using games as a platform for building intelligent embedded agents for the real world. Papers connecting games to all areas of computational intelligence and traditional AI are considered.
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