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Multi-agent cooperation based on behavior prediction and reinforcement learning

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3 Author(s)
Dongyong Yang ; Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China ; Xuejiang Chen ; JingPing Jiang

In multi-agent systems based on reinforcement learning, the evaluation to the behavior of an agent depends on the other agents' behaviors closely. The cooperation performance of multi-agent systems can be improved when each agent takes its action after it predicts the other agents' actions self-consciously. In this paper, several methods for predicting other agents' behaviors were presented, which demand all agents to evaluate the probabilities of actions that other agents may take, and joint-action was introduced to the traditional reinforcement learning. An experiment that three agents cooperate to raise an object was conducted to test the performance of multi-agent systems, and its results show that the cooperation process can be speeded by behavior prediction and joint-action is applied to the traditional reinforcement learning successfully.

Published in:

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on  (Volume:6 )

Date of Conference:

15-19 June 2004

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