J4 ›› 2006, Vol. 28 ›› Issue (2): 107-110.
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王长缨 尹晓虎 鲍翊平 姚莉
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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
王长缨 尹晓虎 鲍翊平 姚莉. 基于随机博弈的Agent协同强化学习方法[J]. J4, 2006, 28(2): 107-110.
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http://joces.nudt.edu.cn/CN/Y2006/V28/I2/107