Learning Attentional Communication for Multi-Agent Cooperation. - Jiechuan Jiang; Zongqing Lu 002 (NeurIPS, 2018)

Graph Convolutional Reinforcement Learning for Multi-Agent Cooperation. - Jiechuan Jiang; Chen Dun; Zongqing Lu 002 (CoRR, 2018)

Learning Fairness in Multi-Agent Systems. - Jiechuan Jiang; Zongqing Lu 002 (NeurIPS, 2019)

Generative Exploration and Exploitation. - Jiechuan Jiang; Zongqing Lu 002 (AAAI, 2020)

Graph Convolutional Reinforcement Learning. - Jiechuan Jiang; Chen Dun; Tiejun Huang 001; Zongqing Lu 002 (ICLR, 2020)

The Emergence of Individuality in Multi-Agent Reinforcement Learning. - Jiechuan Jiang; Zongqing Lu 002 (CoRR, 2020)

The Emergence of Individuality. - Jiechuan Jiang; Zongqing Lu 002 (ICML, 2021)

Model-Based Opponent Modeling. - Xiaopeng Yu 001; Jiechuan Jiang; Haobin Jiang; Zongqing Lu 002 (CoRR, 2021)

Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning. - Yuanpei Chen; Tianhao Wu 001; Shengjie Wang; Xidong Feng; Jiechuan Jiang; Zongqing Lu 002; Stephen McAleer; Hao Dong 003; Song-Chun Zhu; Yaodong Yang 001 (NeurIPS, 2022)

I2Q: A Fully Decentralized Q-Learning Algorithm. - Jiechuan Jiang; Zongqing Lu 002 (NeurIPS, 2022)

Model-Based Opponent Modeling. - Xiaopeng Yu 001; Jiechuan Jiang; Wanpeng Zhang 002; Haobin Jiang; Zongqing Lu 002 (NeurIPS, 2022)

Online Tuning for Offline Decentralized Multi-Agent Reinforcement Learning. - Jiechuan Jiang; Zongqing Lu 002 (AAAI, 2023)

Adaptive Learning Rates for Multi-Agent Reinforcement Learning. - Jiechuan Jiang; Zongqing Lu 002 (AAMAS, 2023)

Offline Decentralized Multi-Agent Reinforcement Learning. - Jiechuan Jiang; Zongqing Lu 002 (ECAI, 2023)

Learning from Visual Observation via Offline Pretrained State-to-Go Transformer. - Bohan Zhou; Ke Li; Jiechuan Jiang; Zongqing Lu 002 (NeurIPS, 2023)

Model-Based Decentralized Policy Optimization. - Hao Luo 011; Jiechuan Jiang; Zongqing Lu 002 (CoRR, 2023)

Multi-Agent Alternate Q-Learning. - Kefan Su; Siyuan Zhou; Jiechuan Jiang; Chuang Gan 001; Xiangjun Wang; Zongqing Lu 002 (AAMAS, 2024)

Opponent Modeling based on Subgoal Inference. - Xiaopeng Yu 001; Jiechuan Jiang; Zongqing Lu 002 (NeurIPS, 2024)

Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey. - Jiechuan Jiang; Kefan Su; Zongqing Lu 002 (CoRR, 2024)

Towards General Computer Control: A Multimodal Agent for Red Dead Redemption II as a Case Study. - Weihao Tan; Ziluo Ding; Wentao Zhang 007; Boyu Li 003; Bohan Zhou; Junpeng Yue; Haochong Xia; Jiechuan Jiang; Longtao Zheng; Xinrun Xu; Yifei Bi; Pengjie Gu; et al. (CoRR, 2024)

A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges. - Xinrun Xu; Yuxin Wang 006; Chaoyi Xu; Ziluo Ding; Jiechuan Jiang; Zhiming Ding; Börje F. Karlsson (CoRR, 2024)

Best Possible Q-Learning. - Jiechuan Jiang; Zongqing Lu 002 (UAI, 2025)