1. Output synchronization of multi-agent systems via reinforcement learning.
- Author
-
Liu, Yingying and Wang, Zhanshan
- Subjects
- *
MULTIAGENT systems , *REINFORCEMENT learning , *MACHINE learning , *SYNCHRONIZATION , *ALGORITHMS - Abstract
In this paper, the measured input–output data sequences with pinning gain are proposed via the topology of multi-agent systems (MAS), where the requirement of reinforcement learning algorithm on internal state is avoided by pinning gain and the measured data of leader and neighbors. Besides, a data-based tracking state is given, which can be applied to MAS with different control matrices. According to the sequences and tracking state, a distributed control policy and corresponding reinforcement learning algorithm are proposed for the output synchronization. The proposed algorithm overcomes the shortcoming that previous algorithms can not be applied to MAS with different control matrices in the absence of model information and full-state vector. Finally, the effectiveness of proposed algorithm is verified by simulation examples. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF