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Game Theory Models for Multi-Robot Patrolling of Infrastructures

机译:基础设施多机器人巡逻的博弈论模型

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This work is focused on the problem of performing multi-robot patrolling for infrastructure security applications in order to protect a known environment at critical facilities. Thus, given a set of robots and a set of points of interest, the patrolling task consists of constantly visiting these points at irregular time intervals for security purposes. Current existing solutions for these types of applications are predictable and inflexible. Moreover, most of the previous work has tackled the patrolling problem with centralized and deterministic solutions and only few efforts have been made to integrate dynamic methods. Therefore, one of the main contributions of this work is the development of new dynamic and decentralized collaborative approaches in order to solve the aforementioned problem by implementing learning models from Game Theory. The model selected in this work that includes belief-based and reinforcement models as special cases is called Experience-Weighted Attraction. The problem has been de...
机译:这项工作侧重于执行基础设施安全应用的多机器人巡逻的问题,以保护在关键设施中的已知环境。因此,给定一组机器人和一组兴趣点,巡逻任务包括以不规则的时间间隔不断访问这些点以供安全目的。目前这些类型的应用的现有解决方案是可预测和不灵活的。此外,最前面的大部分工作都解决了集中和确定性解决方案的巡逻问题,并且只有很少的努力来集成动态方法。因此,这项工作的主要贡献之一是开发新的动态和分散的协作方法,以便通过实施博弈论的学习模型来解决上述问题。在这项工作中选择的模型包括基于信仰和强化模型作为特殊情况称为体验加权吸引力。问题已经......

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