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THE IMPACT OF THE CONFLICT ON SOLVING DISTRIBUTED CONSTRAINT SATISFACTION PROBLEMS

机译:冲突对解决分布式约束满意度问题的影响

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Distributed Constraint Satisfaction Problems (DCSPs) involve a vast number of AI and Multi-Agent problems. Many important efforts have been recently accomplished for solving these kinds of problems using both backtracking-based and mediation-based methods. One of the most successful mediation based algorithms in this field is Asynchronous Partial Overlay (APO) algorithm. By choosing some agents as mediators. APO tries to centralize portions of the distributed problem, and then each mediator tries to solve its centralized sub-problem. This work continues until the whole problem is solved. This paper presents a new strategy to select mediators. The main idea behind this strategy is that the number of mediators conflicts (violated constraints) impacts directly on its performance. Experimental results show that choosing the mediators with the most number of conflicts not only leads to considerable decrease in APO complexity, but also it can decrease the complexity of the other extensions of the APO such as IAPO algorithm. MaxCAPO and MaxCIAPO are two new expansions of APO which introduce this idea and are presented in this article. The results of using this mediator selection strategy show a rapid and desirable improvement over various parameters in comparison with APO and IAPO.
机译:分布式约束满足问题(DCSP)涉及大量的AI和Multi-Agent问题。最近已经完成了许多重要的工作,以使用基于回溯的方法和基于中介的方法来解决此类问题。异步部分重叠(APO)算法是该领域最成功的基于中介的算法之一。通过选择一些代理商作为调解人。 APO尝试集中解决分布式问题的各个部分,然后每个调解员尝试解决其集中的子问题。这项工作将一直持续到解决整个问题为止。本文提出了一种选择调解员的新策略。该策略背后的主要思想是调解员冲突的数量(违反约束条件)直接影响其绩效。实验结果表明,选择冲突最多的介体不仅可以大大降低APO的复杂度,而且可以降低APO其他扩展(如IAPO算法)的复杂度。 MaxCAPO和MaxCIAPO是APO的两个新扩展,介绍了此思想,并在本文中进行介绍。与APO和IAPO相比,使用此介体选择策略的结果显示出对各种参数的快速而理想的改进。

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