摘要
将强化学习引入到进化博弈中,建立了进化博弈中的多代理人强化学习模型,并基于Q-学习给出了算法流程,仿真算例的结果表明多代理人强化学习模型能使得博弈人不断学习、寻求最优策略.
In this paper,reinforcement learning is introduced in evolutionary games,multiagent reinforcement learning-model is presented,and the learning algorithm is given based on Q-learning.The results of simulation experiments show that the multiagent reinforcement learning-model can make agents find the optimal strategy by learning.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2009年第3期28-33,共6页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(60574071
70533040)
关键词
博弈论
进化博弈
强化学习
Q-学习
game theory
evolutionary game
reinforcement learning
Q-learning