Knowledge Commons of Institute of Automation，CAS
| Online Synchronous Approximate Optimal Learning Algorithm for Multiplayer Nonzero-Sum Games With Unknown Dynamics | |
Liu, Derong; Li, Hongliang; Wang, Ding
| |
| 发表期刊 | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
 |
| 2014-08-01 | |
| 卷号 | 44期号:8页码:1015-1027 |
| 文章类型 | Article |
| 摘要 | In this paper, we develop an online synchronous approximate optimal learning algorithm based on policy iteration to solve a multiplayer nonzero-sum game without the requirement of exact knowledge of dynamical systems. First, we prove that the online policy iteration algorithm for the nonzero-sum game is mathematically equivalent to the quasi-Newton's iteration in a Banach space. Then, a model neural network is established to identify the unknown continuous-time nonlinear system using input-output data. For each player, a critic neural network and an action neural network are used to approximate its value function and control policy, respectively. Our algorithm only needs to tune the weights of critic neural networks, so there will be less computational complexity during the learning process. All the neural network weights are updated online in real-time, continuously and synchronously. Furthermore, the uniform ultimate bounded stability of the closed-loop system is proved based on Lyapunov approach. Finally, two simulation examples are given to demonstrate the effectiveness of the developed scheme. |
| 关键词 | Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Multiplayer Nonzero-sum Games Neural Networks Neuro-dynamic Programming Policy Iteration |
| WOS标题词 | Science & Technology ; Technology |
| 关键词[WOS] | TIME NONLINEAR-SYSTEMS ; H-INFINITY CONTROL ; ADAPTIVE CRITIC DESIGNS ; POLICY ITERATION ; FEEDBACK-CONTROL ; CONTROL SCHEME ; REINFORCEMENT ; STATE ; CONTROLLER ; EQUATIONS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| WOS类目 | Automation & Control Systems ; Computer Science, Cybernetics |
| WOS记录号 | WOS:000342278500004 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/3845 |
| 专题 | 多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队 |
| 作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 第一作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Liu, Derong,Li, Hongliang,Wang, Ding. Online Synchronous Approximate Optimal Learning Algorithm for Multiplayer Nonzero-Sum Games With Unknown Dynamics[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2014,44(8):1015-1027. |
| APA | Liu, Derong,Li, Hongliang,&Wang, Ding.(2014).Online Synchronous Approximate Optimal Learning Algorithm for Multiplayer Nonzero-Sum Games With Unknown Dynamics.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,44(8),1015-1027. |
| MLA | Liu, Derong,et al."Online Synchronous Approximate Optimal Learning Algorithm for Multiplayer Nonzero-Sum Games With Unknown Dynamics".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 44.8(2014):1015-1027. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| [00-J-2014-TSMC] Onl（20912KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 | |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论