Token approach for role allocation in extreme teams: analysis and experimental evaluation

P. Scerri, A. Farinelli, Steven Okamoto, Milind Tambe
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引用次数: 23

Abstract

Open computational systems comprise physical entities coordinating their activities in dynamic environments. Many exciting applications require a large number of such entities to achieve team coordination in complex missions execution. To meet the fundamental challenge of role allocation in such extreme teams, we propose an algorithm called LA-DCOP, that overcomes the limitations of previous algorithms by incorporating three key ideas. First, we represent the role allocation problem as a distributed constraint optimization problem and use tokens representing roles to minimize constraint violations. Second, we use probabilistic information about the team to guide the search quickly towards good solutions. Third, we designed the algorithm to manage constrained roles. We show that LA-DCOP not only meets our requirements in extreme teams, but also compares favorably against previous role allocation algorithms. LA-DCOP has allowed an order of magnitude scale-up in extreme teams, with role allocation in a fully distributed proxy-based teams with up to 200 members.
极端团队角色分配的Token方法:分析与实验评价
开放计算系统包括在动态环境中协调其活动的物理实体。许多令人兴奋的应用程序需要大量这样的实体来实现复杂任务执行中的团队协调。为了应对这种极端团队中角色分配的基本挑战,我们提出了一种称为LA-DCOP的算法,该算法通过结合三个关键思想来克服以前算法的局限性。首先,我们将角色分配问题表示为分布式约束优化问题,并使用表示角色的令牌来最小化约束违规。其次,我们使用关于团队的概率信息来指导搜索快速找到好的解决方案。第三,设计了约束角色管理算法。我们的研究表明,LA-DCOP不仅满足了我们在极端团队中的要求,而且与以前的角色分配算法相比也具有优势。LA-DCOP允许在极端团队中进行数量级扩展,在完全分布式的基于代理的团队中分配角色,最多可容纳200名成员。
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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