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A Robust Planning Algorithm for Groups of Entities in Discrete Spaces

机译:离散空间中实体组的鲁棒规划算法

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Automated planning is a well-established field of artificial intelligence (AI), with applications in route finding, robotics and operational research, among others. The task of developing a plan is often solved by finding a path in a graph representing the search domain; a robust plan consists of numerous paths that can be chosen if the execution of the best (optimal) one fails. While robust planning for a single entity is rather simple, development of a robust plan for multiple entities in a common environment can lead to combinatorial explosion. This paper proposes a novel hybrid approach, joining heuristic search and the wavefront algorithm to provide a plan featuring robustness in areas where it is needed, while maintaining a low level of computational complexity.
机译:自动化规划是一个成熟的人工智能(AI)领域,其应用包括路线查找,机器人技术和运筹学等。制定计划的任务通常可以通过在表示搜索域的图中找到路径来解决。一个健壮的计划包含许多路径,如果执行最佳(最优)的路径失败,则可以选择这些路径。尽管针对单个实体的健壮计划相当简单,但是在公共环境中为多个实体制定健壮计划可能会导致组合爆炸。本文提出了一种新颖的混合方法,结合启发式搜索和波前算法,以提供一种在需要的地方具有鲁棒性的计划,同时保持较低的计算复杂度。

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