• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2006, Vol. 28 ›› Issue (2): 107-110.

• 论文 • 上一篇    下一篇

基于随机博弈的Agent协同强化学习方法

王长缨 尹晓虎 鲍翊平 姚莉   

  • 出版日期:2006-02-01 发布日期:2010-05-20

  • Online:2006-02-01 Published:2010-05-20

摘要:

本文针对一类追求系统得益最大化的协作团队的学习问题,基于随机博弈的思想,提出了一种新的多Agent协同强化学习方法。协作团队中的每个Agent通过观察协作相识者的 历史行为,依照随机博弈模型预测其行为策略,进而得出最优的联合行为策略。

关键词: 强化学习 多agent系统 随机博弈 协作

Abstract:

This paper aims at the learning process of a kind of cooperative teams, which pursue the maximum  benefit of a whole system. We propose a new cooperat ive reinforcement learning method based on the stochastic game in multi-agent systems. Each agent of the team decides its behaviors after forecasting the behavior strategy of acquaintances according to the stochastic game structure and their historical behaviors, and then a jointly optimal behavior stra tegy is obtained.

Key words: reinforcement learning, multi-agent system, stochastic game, cooperation