A multi-agent reinforcement learning algorithm based on Stackelberg game

Abstract

Multi-agent reinforcement learning has been paid much attention due to its wide applications in various engineering systems. In this paper, the control problems of large-scale multi-agent systems with multiple roles are formulated into a multiplayer Stackelberg game, which provides a new perspective on cooperative issues. Then a Stackelberg Q-learning… (More)

Topics

6 Figures and Tables

Cite this paper

@article{Cheng2017AMR, title={A multi-agent reinforcement learning algorithm based on Stackelberg game}, author={Chi Cheng and Zhangqing Zhu and Bo Xin and Chunlin Chen}, journal={2017 6th Data Driven Control and Learning Systems (DDCLS)}, year={2017}, pages={727-732} }