Abstract
This paper investigates the approximate calculation problem of noninferior Nash equilibrium (NNE) in multi-team game. Combined with variational inequalities theory, Nash equilibrium theory, and dynamic system theory, a projection neural network (PNN) algorithm for computing NNE of multi-team game with smooth payoff functions is derived. Utilizing stable theory, stability criteria of NNE in multi-team game are further given. As an application, a flow control model of parallel-link communication networks based on multi-team game and neural network algorithm is elaborated. Finally, a simulation result for two teams, two communication links, and two users in each team parallel-linkcommunication network is also given to illustrate the effectiveness of the PNN algorithm proposed in this paper.
This work is supported by National Nature Science Foundation of China under Grants 62062018, 61472093, 11461082, 11761018, Guizhou Province University Science and Technology Top Talents Project KY2018047, Guizhou University of Finance and Economics 2018XZD01, Science and Technology Planning Project of Guizhou Province of China under Grants [2017] 1016, the Innovation Exploration and Academic New Seedling Project of Guizhou University of Finance and Economics (No. Qian Ke He Ping Tai Ren Cai [2017] 5736-025), and Guizhou Key Laboratory of Big Data Statistics Analysis (No.: Guizhou Science and Technology Cooperation Platform Talent [2019] 5103).
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Liu, Z., Yang, H., Xiong, L. (2021). Neural Network Algorithm of Multi-team Game and Its Application in Parallel-Link Communication Networks Flow Control. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 369. Springer, Cham. https://doi.org/10.1007/978-3-030-72792-5_62
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