Here is a list of research projects that use OpenRL. If you use OpenRL in your research projects, feel free to tell us about it and join the list.
Description: TiZero is a reinforcement learning agent for Google Research Football full game, trained with distributed self-play.
- Paper: TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play(AAMAS 2023)
- Authors: Fanqi Lin, Shiyu Huang, Tim Pearce, Wenze Chen, Wei-Wei Tu
- Github: https://github.com/OpenRL-Lab/TiZero
Description: Recent algorithms designed for reinforcement learning tasks focus on finding a single optimal solution. However, in many practical applications, it is important to develop reasonable agents with diverse strategies. In this paper, we propose an on-policy framework for discovering multiple strategies for the same task. Experimental results show that our method efficiently finds diverse strategies in a wide variety of reinforcement learning tasks.
- Paper: DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization(AAMAS Extended Abstract 2023)
- Authors: Wenze Chen, Shiyu Huang, Yuan Chiang, Ting Chen, Jun Zhu