Abstract
In this paper, the distributed optimization problem for multi-agent system with time-varying communication delay \(\tau (t)\) is studied based on game theory. Firstly, the distributed optimization problem \(\min _{x} \phi (x)\) is modeled as a state based ordinal potential game model G. Then, the existence and validity of the Nash equilibrium in the game model are verified. In addition, a revenue-based strategy learning algorithm is designed under topology network with \(\tau (t)\) to find the Nash equilibrium. Finally, a numerical simulation illustrates the results.
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Acknowledgements
This work was supported by the Open Fund of Key Laboratory of Dependable Service Computing in Cyber Physical Society of Chongqing University (Grant No. CPSDSC202202), and the National Natural Science Foundation of China (Grant No. 62103203).
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Wang, C., Zhu, R., Wang, F., Liu, Z. (2023). Distributed Optimization Algorithm for Multi-agent System with Time-Varying Communication Delay Based on the Game Theory. In: Jia, Y., Zhang, W., Fu, Y., Wang, J. (eds) Proceedings of 2023 Chinese Intelligent Systems Conference. CISC 2023. Lecture Notes in Electrical Engineering, vol 1089. Springer, Singapore. https://doi.org/10.1007/978-981-99-6847-3_62
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DOI: https://doi.org/10.1007/978-981-99-6847-3_62
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