多智能体系统的进化合作机制

Renping Liu, Yuehai Wang
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引用次数: 1

摘要

研究了多智能体系统(MAS)合作共赢任务的最优解,并针对多智能体觅食的典型案例建立了自动协商互惠机制。建立了MAS中的agent与博弈论中的参与人的等价关系、MAS中的最优解与博弈论中的均衡关系、MAS中的合作任务与多阶段马尔可夫博弈关系。针对均衡选择的困难,从进化博弈论的角度建立了一种不相关的不对称博弈——鹰鸽博弈模型。在此基础上,提出了一种基于复制因子动态的自执行合作算法,寻找鹰鸽博弈的进化稳定策略。仿真验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Evolutionary Cooperative Mechanism for Multi-agent System
The optimal solution for the cooperation win-win task for Multi-agent system (MAS) was studied and a automatic negotiation reciprocal mechanism was build in this paper for the typical case of multi- agent foraging. The equivalences between agent in MAS and player in game theory, optimal solution in MAS and equilibrium in game theory, and cooperation task in MAS and multi-stage Markov game were then established. To the difficulties of equilibriums selection, a hawk dove game model, which is a uncorrelated asymmetry game, is build from the point view of evolutionary game theory. And a self-enforcing cooperative algorithm based on replicator dynamic was proposed to find the evolutionary stable strategy of hawk dove game. The simulation verified the effectiveness of the proposed approach.
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