JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2010, Vol. 40 ›› Issue (6): 8-11.

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Multiagent cooperation learning based on an evolutional algorithm

WANG Yun, WANG Jun, HAN Wei*   

  1. School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210046, China
  • Received:2010-02-27 Online:2010-12-16 Published:2010-02-27

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Abstract:

Reinforcement learning is  not applicable concerning large state-actions, since that its convergence speed increases exponentially with the number of dimensions of state-action space. In many situations, this problem partially can be solved  by utilizing a cooperation relationship among agents. An evolutional algorithm was put forward, which could rapidly find the effective updating of state-action pairs by the evolutionary operators such as reproduction as well as die out. Simulations proved that the algorithm performs was better than present multiagent cooperation learning algorithms.

Key words:  multiagent system, cooperation learning, evolutionary algorithm

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