Extended Increasing Cost Tree Search for Non-Unit Cost Domains

Extended Increasing Cost Tree Search for Non-Unit Cost Domains
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非单位成本域的扩展递增成本树搜索

DOI:
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发表时间:
2018
期刊:
International Joint Conference on Artificial Intelligence
影响因子:
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通讯作者:
Ariel Felner
Ariel Felner
中科院分区:
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文献类型:
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作者:
Thayne T. Walker;Nathan R Sturtevant;Ariel Felner

文献摘要

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多代理探路(MAPF)具有应用程序 在导航,机器人技术,游戏和计划中。最多 处理基于搜索的最佳算法 MAPF专注于具有单元的简单域 成本操作和单位时间步骤。虽然这些 约束保留算法的许多方面 简单,它们还严重限制了 可以使用。在本文中,我们介绍了一个新的定义 MAPF问题的非单位成本和 非单位时间步长域以及新的多种多样 这些国家继任者的生成计划 域。最后,我们定义了扩展版本 成本不断增加的树搜索算法(ICT) 对于非单位成本,有两个新的次级变体 ICT:Epsilon-Ict和W-Icts。我们的实验 证明较高质量的亚最佳解决方案 可以在分散的域中实现 移动模型在不超过 域中的低质量,最佳解决方案 粗离散的运动模型。
Multi-agent pathfinding (MAPF) has applications in navigation, robotics, games and planning. Most work on search-based optimal algorithms for MAPF has focused on simple domains with unit cost actions and unit time steps. Although these constraints keep many aspects of the algorithms simple, they also severely limit the domains that can be used. In this paper we introduce a new definition of the MAPF problem for non-unit cost and non-unit time step domains along with new multiagent state successor generation schemes for these domains. Finally, we define an extended version of the increasing cost tree search algorithm (ICTS) for non-unit costs, with two new sub-optimal variants of ICTS: epsilon-ICTS and w-ICTS. Our experiments show that higher quality sub-optimal solutions are achievable in domains with finely discretized movement models in no more time than lower-quality, optimal solutions in domains with coarsely discretized movement models.