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Selective Smooth Fictitious Play: An approach based on game theory for patrolling infrastructures with a multi-robot system

机译：选择性平滑虚拟游戏：一种基于博弈论的方法，用于使用多机器人系统巡逻基础设施

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摘要

The multi-robot patrolling problem is defined as the activity of traversing a given environment. In this activity, a fleet of robots visits some places at irregular intervals of time for security purpose. To date, this problem has been solved with different approaches. However, the approaches that obtain the best results are unfeasible for security applications because they are centralized and deterministic. To overcome the disadvantages of previous work, this paper presents a new distributed and non-deterministic approach based on a model from game theory called Smooth Fictitious Play. To this end, the multi-robot patrolling problem is formulated by using concepts of graph theory to represent an environment. In this formulation, several normal-form games are defined at each node of the graph. This approach is validated by comparison with best suited literature approaches by using a patrolling simulator. The results for the proposed approach turn out to be better than previous literature approaches in as many as 88% of the cases of study. Moreover, the novel approach presented in this work has many advantages over other approaches of the literature such distribution, robustness, scalability, and dynamism. The achievements obtained in this work validate the potential of game theory to protect infrastructures. © 2013 Elsevier Ltd. All rights reserved.
机译：多机器人巡逻问题定义为遍历给定环境的活动。在此活动中，出于安全目的，一群机器人会不定期地访问某些地方。迄今为止，已经用不同的方法解决了这个问题。但是，获得最佳结果的方法对于安全性应用是不可行的，因为它们是集中式的和确定性的。为了克服以前的工作的弊端，本文提出了一种新的分布式不确定性方法，该方法基于博弈论中称为“平滑虚拟游戏”的模型。为此，通过使用图论的概念来表示环境来提出多机器人巡逻问题。在此公式中，在图的每个节点上定义了几个标准形式的博弈。通过使用巡逻模拟器与最适合的文献方法进行比较，验证了该方法。在多达88％的研究案例中，提出的方法的结果都比以前的文献方法更好。此外，与文献中的其他方法相比，本文中提出的新颖方法具有许多优势，例如分布，鲁棒性，可伸缩性和动态性。这项工作取得的成就证明了博弈论保护基础设施的潜力。 ©2013 ElsevierLtd。保留所有权利。

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