@inproceedings{395e3e6de16f45d28cd930decf5a0159,
title = "Two-Stage Value Iteration for Multi-Leader Tracking under Interactive Nash Equilibrium in Discrete Time",
abstract = "For the discrete-time multi-leader system, this paper proposes a two-stage value iteration to fit complex optimal solutions in Bellman equations of multi-leader and realize the tracking target under multi-leader. The two-stage value iteration algorithm adds a sub-iteration that is proposed for obtaining the control strategy. Through this iteration strategy, the optimal control strategy is acquired and the system realizes interactive Nash equilibrium. In this research, we attempt to utilize a critic network for the purpose of fitting the value index as well as an actor network to fit the control strategy. With these two neural networks, we don't need to know the specific system, and the algorithm can be driven by data. At last, simulation results indicate the feasibility of the algorithm.",
keywords = "ADP, Nash Equilibrium, Two-stage iteration, Value Iteration, multi-leader System",
author = "Shangning Liu and Xiaoli Wang and Mu Yan and Yiwen Ma",
note = "Publisher Copyright: {\textcopyright} 2025 Technical Committee on Control Theory, Chinese Association of Automation.; 44th Chinese Control Conference, CCC 2025 ; Conference date: 28-07-2025 Through 30-07-2025",
year = "2025",
doi = "10.23919/CCC64809.2025.11179402",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "1656--1661",
editor = "Jian Sun and Hongpeng Yin",
booktitle = "Proceedings of the 44th Chinese Control Conference, CCC 2025",
address = "美国",
}