Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (1): 217-224.

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Confrontation simulation for network information system-of-systems based on Nash-Q

YAN Xuefei, LI Xinming, LIU Dong, WANG Shoubiao   

  1. Science and Technology on Complex Electronic System Simulation Laboratory, Equipment Academy, Beijing 101416, China
  • Online:2018-01-08 Published:2018-01-08

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Abstract:

Battle simulation for weapon equipment sysem-of-systems (SoS) belongs to the research category of complex system and the confrontation cognition of network information system-of-systems (NISoS) based on Nash-Q technology is researched. The form of the Nash-Q is similar with the union Q-learning except the obtaining of the union policy. For the zero-sum game model of the SoS battle simulation, the realization and solution of the Nash-Q model is more effective since the Nash-Q does not need the history action messages of other Agents. The zero-sum game command model for the battle simulation of the tactical command level is built and the solving process of Nash-equilibrium is introduced through the complete information of other Agents is not known. The Gauss radial basis function neural network is used to discrete the Q-table to improve the discrete performance and generalization ability of Nash-Q. Finally, the effectiveness of the algorithm is validated through battle simulation of NISoS. Compared with Q-learning and Rule-based algorithm, the proposed algorithm has higher gains and can be used to off-line decision.

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