An Evolutionary Game Coordinated Control Approach to Division of Labor in Multi-Agent Systems
An Evolutionary Game Coordinated Control Approach to Division of Labor in Multi-Agent Systems
复制标题
多智能体系统分工的进化博弈协调控制方法
DOI：
10.1109/access.2019.2938254
复制
发表时间：
2019-01-01
期刊：
影响因子：
3.9
通讯作者：
Du, Jinming
中科院分区：
文献类型：
--
作者：
Du, Jinming
在本文中，我们提出了一个进化博弈论的方法来协调控制的多智能体系统。在这个数学框架中，智能体与网络上的邻居进行博弈，并通过局部交互来更新策略。为了使系统达到一定的控制目标，需要选择合适的博弈类型，设计适应度的计算和评价方法，指定交互约束和更新规则。在系统的演化过程中，智能体没有预先设计的动力学方程。他们独立地调整自己的行为，以增加自己的利益。系统在个体交互和自主决策的过程中达到最终状态。以劳动分工问题为例，我们详细说明了所提出的控制方法。通过对正则图、一般连通图和异构无标度网络的仿真，验证了理论方法的有效性。
In this paper, we propose an evolutionary game theoretic approach to coordinated control of multi-agent systems. In this mathematical framework, agents play games with their neighbors on the network, and update strategies through local interaction. In order to achieve a certain control objective of the system, we need to select the appropriate game type, design the calculation and evaluation methods of fitness, specify the interactive constraints and updating rules. During the evolutionary process of the system, agents have no predesigned dynamical equations. They adjust their behavior independently for the purpose of increasing their own benefits. The system achieves its final state in the process of individual interaction and autonomous decision-making. Taking division of labor problem as an example, we demonstrate the proposed control approach in detail. The performance of the theoretical method is verified by simulation on the regular graph, the general connected graphs, and heterogeneous scale-free networks, respectively.