Chinese Journal of Intelligent Science and Technology ›› 2020, Vol. 2 ›› Issue (4): 394-400.doi: 10.11959/j.issn.2096-6652.202042

• Special Issue: Deep Reinforcement Learning • Previous Articles     Next Articles

Output synchronization of heterogeneous multi-agent system:a reinforcement learning approach based on data

Yingying LIU, Zhanshan WANG   

  1. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Revised:2020-12-01 Online:2020-12-15 Published:2020-12-01
  • Supported by:
    The National Natural Science Foundation of China(61973070);Liaoning Revitalization Talents Program(XLYC1802010);SAPI Fundamental Research Funds(2018ZCX22)


The output synchronization of heterogeneous multi-agent system was studied by reinforcement learning.According to the topology of multi-agent system, the performance index and value function with neighbor control input were defined.To overcome the disadvantage of existing control methods that require system model, a reinforcement learning algorithm based on system data was proposed.Hence, the output synchronization controller can also be applied when the system model was unknown.In addition, by adjusting the weight matrix in value function, the control cost of each agent can be reduced.Finally, a simulation example was given to illustrate the effectiveness of proposed method and the superiority of defined value function.

Key words: multi-agent system, reinforcement learning, output synchronization, based on data

CLC Number: 

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