首页> 外文期刊>The Journal of Artificial Intelligence Research >Implicitly Coordinated Multi-Agent Path Finding under Destination Uncertainty: Success Guarantees and Computational Complexity
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Implicitly Coordinated Multi-Agent Path Finding under Destination Uncertainty: Success Guarantees and Computational Complexity

机译:在目的地不确定性下隐式协调的多智能路径查找:成功保证和计算复杂性

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摘要

In multi-agent path finding (MAPF), it is usually assumed that planning is performed centrally and that the destinations of the agents are common knowledge. We will drop both assumptions and analyze under which conditions it can be guaranteed that the agents reach their respective destinations using implicitly coordinated plans without communication. Furthermore, we will analyze what the computational costs associated with such a coordination regime are. As it turns out, guarantees can be given assuming that the agents are of a certain type. However, the implied computational costs are quite severe. In the distributed setting, we either have to solve a sequence of NP-complete problems or have to tolerate exponentially longer executions. In the setting with destination uncertainty, bounded plan existence becomes PSPACE-complete. This clearly demonstrates the value of communicating about plans before execution starts.
机译:在多代理路径查找(MAPF)中,通常假设规划是集中的,并且代理的目的地是常识。 我们将放弃两个假设和分析,在这种情况下,可以保证代理商在没有沟通的情况下使用隐式协调的计划达到各自的目的地。 此外,我们将分析与这种协调制度相关的计算成本是什么。 事实证明,假设药剂具有某种类型,可以给出保证。 但是,隐含的计算成本非常严重。 在分布式设置中,我们要么必须解决一系列NP完整的问题,或者必须容忍指数较长的执行。 在具有目的地不确定性的设置中,有界计划的存在成为PSPace-Tress。 这清楚地展示了在执行开始前沟通计划的价值。

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