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Variants of Independence Detection in SAT-Based Optimal Multi-agent Path Finding

机译:基于SAT的最佳多智能体路径查找中独立检测的变体

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In multi-agent path finding (MAPF) on graphs, the task is to find paths for distinguishable agents so that each agent reaches its unique goal vertex from the given start while collisions between agents are forbidden. A cumulative objective function is often minimized in MAPF. The main contribution of this paper consists in integrating independence detection technique (ID) into a compilation-based MAPF solver that translates MAPF instances into prepositional satisfiability (SAT). The independence detection technique in search-based solvers tries to decompose a given MAPF instance into instances consisting of small groups of agents with no interaction across groups. After the decomposition phase, small instances are solved independently and the solution of the original instance is combined from individual solutions to small instances. The presented experimental evaluation indicates significant reduction of the size of instances translated to the target SAT formalism and positive impact on the overall performance of the solver.
机译:在图上的多智能体路径查找(MAPF)中,任务是为可区分的智能体找到路径,以便每个智能体从给定的起点开始达到其唯一的目标顶点,同时禁止智能体之间的冲突。累积目标函数通常在MAPF中被最小化。本文的主要贡献在于将独立性检测技术(ID)集成到基于编译的MAPF求解器中,该求解器将MAPF实例转换为介词可满足性(SAT)。基于搜索的求解器中的独立性检测技术试图将给定的MAPF实例分解为由少量代理组成的实例,这些代理之间没有任何交互。在分解阶段之后,小实例将独立求解,原始实例的解决方案将从单个解决方案组合到小实例。提出的实验评估表明,转换为目标SAT形式主义的实例数量显着减少,并且对求解器的整体性能产生了积极影响。

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