Effective Task Allocation by Enhancing Divisional Cooperation in Multi-Agent Continuous Patrolling Tasks
Effective Task Allocation by Enhancing Divisional Cooperation in Multi-Agent Continuous Patrolling Tasks
复制标题
多智能体连续巡逻任务中加强分工合作实现有效任务分配
DOI：
10.1109/ictai.2016.0016
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Sea Vourchteang and Toshiharu Sugawara
中科院分区：
文献类型：
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作者：
Ayumi Sugiyama;Sea Vourchteang and Toshiharu Sugawara
本文提出了一种有效的自治任务分配方法，可以实现多智能体环境下的分工合作，高效的合作工作。计算机和网络技术使智能体/机器人能够自主行为，并用于清洁和安全巡逻等各种应用。然而，覆盖大的环境，几个代理之间的合作和协作是强制性的效率和所需的任务质量。然而，如何代理合作是一个具有挑战性的问题，因为实际的环境通常是复杂的，因为他们自己的（非常罕见的）特性。因此，我们首先定义了连续的合作巡逻问题，在该问题中，代理分裂和移动的环境与所需的频率，定义为每个位置。然后，我们扩展了以前的合作方法，以促进自主和有效的分工，通过引入谈判的任务（重新）分配。我们的实验表明，代理与我们的方法，使有效的分工和公平分配，通过确定自己的负责位置在自下而上的方式，他们可以实现大大改善的结果相比，以前的方法。我们还研究了合作机制的结构，并分析了为什么我们的方法可以实现有效的任务分配。
This paper proposes an effective autonomous task allocation method that can achieve efficient cooperative work by divisional cooperation in multi-agent contexts. Computer and network technology has enabled agents/robots to behave autonomously and to be used in a variety of applications such as cleaning and security patrolling. However, to cover large environments, cooperation and collaboration among several agents are mandatory for efficiency and for the required task quality. However, how agents cooperate is a challenging issue because actual environments are usually complicated and because their own (very uncommon) characteristics. Thus, we first define the continuous cooperative patrolling problem, in which agents split up and move around the environments with the required frequencies that are defined for every location. Then, we extend the previous cooperation method to prompt autonomous and effective division of labor by introducing the negotiation for task (re) allocations. We experimentally show that agents with our method enable effective division and fair allocation by identifying their own responsible locations in a bottom-up manner and that they could achieve considerably improved results compared with those of the previous method. We also investigated the structure of the resulting regime for cooperation and analyzed why our method could achieve the effective task allocation.