1 citations · 2 across the 6 of their papers we have counts for
6 papers
Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
Chenxu Wang, Yonggang Jin, Cheng Hu +7
Adapting a single agent to a new multi-agent system brings challenges, necessitating adjustments across various tasks, environments, and interactions with unknown teammates and opp…
RL-LLM-DT: An Automatic Decision Tree Generation Method Based on RL Evaluation and LLM Enhancement
Junjie Lin, Jian Zhao, Lin Liu +6
Traditionally, AI development for two-player zero-sum games has relied on two primary techniques: decision trees and reinforcement learning (RL). A common approach involves using a…
DanZero: Mastering GuanDan Game with Reinforcement Learning
Yudong Lu, Jian Zhao, Youpeng Zhao +2
Card game AI has always been a hot topic in the research of artificial intelligence. In recent years, complex card games such as Mahjong, DouDizhu and Texas Hold'em have been solve…
DouZero+: Improving DouDizhu AI by Opponent Modeling and Coach-guided Learning
Youpeng Zhao, Jian Zhao, Xunhan Hu +2
Recent years have witnessed the great breakthrough of deep reinforcement learning (DRL) in various perfect and imperfect information games. Among these games, DouDizhu, a popular c…
Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents
Jian Zhao, Youpeng Zhao, Weixun Wang +5
Multi-agent reinforcement learning is difficult to be applied in practice, which is partially due to the gap between the simulated and real-world scenarios. One reason for the gap…
MCMARL: Parameterizing Value Function via Mixture of Categorical Distributions for Multi-Agent Reinforcement Learning
Jian Zhao, Mingyu Yang, Youpeng Zhao +4
In cooperative multi-agent tasks, a team of agents jointly interact with an environment by taking actions, receiving a team reward and observing the next state. During the interact…