14 citations · 50 across the 14 of their papers we have counts for
4 papers · 2 filters
Fictitious Cross-Play: Learning Global Nash Equilibrium in Mixed Cooperative-Competitive Games
Zelai Xu, Yancheng Liang, Chao Yu +2
Self-play (SP) is a popular multi-agent reinforcement learning (MARL) framework for solving competitive games, where each agent optimizes policy by treating others as part of the e…
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Zelai Xu, Chao Yu, Fei Fang +2
Agents built with large language models (LLMs) have shown great potential across a wide range of domains. However, in complex decision-making tasks, pure LLM-based agents tend to e…
Automatic Truss Design with Reinforcement Learning
Weihua Du, Jinglun Zhao, Chao Yu +7
Truss layout design, namely finding a lightweight truss layout satisfying all the physical constraints, is a fundamental problem in the building industry. Generating the optimal la…
Learning Zero-Shot Cooperation with Humans, Assuming Humans Are Biased
Chao Yu, Jiaxuan Gao, Weilin Liu +5
There is a recent trend of applying multi-agent reinforcement learning (MARL) to train an agent that can cooperate with humans in a zero-shot fashion without using any human data.…