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Robust Strategy Optimization of Networked Evolutionary Games with Disturbance Inputs

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Abstract

This paper investigates the robust strategy optimization problem for networked evolutionary games (NEGs) with pseudo-players and disturbance inputs using semi-tensor product of matrices, and presents a number of new results. First, we convert the evolutionary dynamics of the NEGs into an algebraic formulation. Secondly, we calculate the profile set in which the total payoff of the game will not less than a given value, and give two algorithms to find the largest robust profile control invariant set and the robust convergence region of this invariant set. Thirdly, the design method of profile feedback control, which can be used to regulate the strategies of the pseudo-players, is given to make the overall benefit of the game reach a certain threshold. Finally, an illustrative example is given to show the effectiveness of our main results.

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Code Availability

The code written for this study is available from the corresponding author on reasonable request.

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Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 62103176) and Natural Science Foundation of Shandong Province (Grant No. ZR2019BF023).

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Authors and Affiliations

  1. School of Mathematics Science, Liaocheng University, Liuyuan Street, Liaocheng City, 252000, Shandong Province, China

    Yuan Zhao, Shihua Fu, Jianli Zhao & Xinling Li

Authors
  1. Yuan Zhao
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  2. Shihua Fu
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  3. Jianli Zhao
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  4. Xinling Li
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Contributions

Yuan Zhao and Shihua Fu performed theoretical analysis and wrote the first draft, Xinling Li wrote and modified the two algorithms, and Shihua Fu and Jianli Zhao contributed to the revision of the manuscript.

Corresponding author

Correspondence to Shihua Fu.

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The authors have no conflicts of interest and did not perform research involving human participants and/or animals.

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Zhao, Y., Fu, S., Zhao, J. et al. Robust Strategy Optimization of Networked Evolutionary Games with Disturbance Inputs. Dyn Games Appl 14, 508–523 (2024). https://doi.org/10.1007/s13235-022-00473-9

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