Compact Representations of Cooperative Path-Finding as SAT Based on Matchings in Bipartite Graphs

Pavel Surynek
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引用次数: 41

Abstract

This paper addresses make span optimal solving of cooperative path-finding problem (CPF) by translating it to propositional satisfiability (SAT). The task is to relocate set of agents to given goal positions so that they do not collide with each other. A novel SAT encoding of CPF is suggested. The novel encoding uses the concept of matching in a bipartite graph to separate spatial constraint of CPF from consideration of individual agents. The separation allowed reducing the size of encoding significantly. The conducted experimental evaluation shown that novel encoding can be solved faster than existing encodings for CPF and also that the SAT based methods dominates over A* based methods in environment densely occupied by agents.
基于二部图匹配的协同寻径压缩表示
本文将合作寻径问题(CPF)转化为命题可满足性问题(SAT),研究了CPF的跨度最优解。任务是将一组智能体重新定位到给定的目标位置,使它们不会相互碰撞。提出了一种新的CPF的SAT编码方法。该编码方法利用二部图匹配的概念,将CPF的空间约束从个体主体的考虑中分离出来。这种分离可以显著减少编码的大小。实验结果表明,在agent密集的环境下,基于SAT的CPF编码方法优于基于A*的CPF编码方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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