Publications (4)
Mastering Asymmetrical Multiplayer Game with Multi-Agent Asymmetric-Evolution Reinforcement Learning
Chenglu Sun, Yichi Zhang, Yu Zhang +4
Asymmetrical multiplayer (AMP) game is a popular game genre which involves multiple types of agents competing or collaborating with each other in the game. It is difficult to train…
Complex Instruction Following with Diverse Style Policies in Football Games
Chenglu Sun, Shuo Shen, Haonan Hu +2
Despite advancements in language-controlled reinforcement learning (LC-RL) for basic domains and straightforward commands (e.g., object manipulation and navigation), effectively ex…
Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs
Chenglu Sun, Shuo Shen, Sijia Xu +1
Training AI with strong and rich strategies in multi-agent environments remains an important research topic in Deep Reinforcement Learning (DRL). The AI's strength is closely relat…
Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement Learning
Chenglu Sun, Shuo Shen, Wenzhi Tao +2
Symbolic regression (SR) has emerged as a pivotal technique for uncovering the intrinsic information within data and enhancing the interpretability of AI models. However, current s…