Research Article
Neural Network Algorithm of Multi-team Game and Its Application in Parallel-Link Communication Networks Flow Control
@INPROCEEDINGS{10.1007/978-3-030-72792-5_62, author={Zixin Liu and Huawei Yang and Lianglin Xiong}, title={Neural Network Algorithm of Multi-team Game and Its Application in Parallel-Link Communication Networks Flow Control}, proceedings={Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part I}, proceedings_a={SIMUTOOLS}, year={2021}, month={4}, keywords={Projection neural network Multi-team game Noninferior Nash equilibrium Variational inequalities Flow control Parallel-link communication networks}, doi={10.1007/978-3-030-72792-5_62} }- Zixin Liu
Huawei Yang
Lianglin Xiong
Year: 2021
Neural Network Algorithm of Multi-team Game and Its Application in Parallel-Link Communication Networks Flow Control
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-72792-5_62
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.
