Introduction

Embodied Decision Intelligence Lab (EDI Lab) belongs to Tsinghua University Shenzhen International Graduate School. It is supersised by Prof. Chao Yu (于超). Our lab is committed to research related to reinforcement learning infrastructure, strategic agent and embodied AI.

Chao Yu is an Associate Professor at Tsinghua University, SIGS. She is also the chairman of the Tsinghua Shenzhen International Graduate School - AgiBot Joint Research Center for Embodied Cognition and Decision Systems (JCES). As first author or corresponding author, Prof. Chao Yu has published more than 50 papers in top-tier international conferences and journals, including ICML, NeurIPS, ICLR, CVPR, ECCV, CoRL, IROS, ICRA, TMLR, and RAL, with over 6,000 citations on Google Scholar.My representative works include the multi-agent reinforcement learning algorithm MAPPO, which has received more than 3,000 Google Scholar citations, and RLinf, a large-scale reinforcement learning training framework for embodied intelligence, which has accumulated over 3,000 GitHub stars.

Our lab is currently recruiting Master’s students, Ph.D. students, joint-program Ph.D. students with Zhongguancun Academy, postdoctoral researchers, and undergraduate research assistants. We warmly welcome students who are interested in recommended admission or applying through the graduate entrance examination to SIGS programs such as Artificial Intelligence, Data Science and Information Technology, Big Data Engineering, and Electronic Engineering, as well as applicants for the above Ph.D. and postdoctoral positions, to join us.

Highlights

VS-Bench: Evaluating VLMs for Strategic Reasoning and Decision-Making in Multi-Agent Environments

Zelai Xu, Zhexuan Xu, Xiangmin Yi, Huining Yuan, Xinlei Chen, Yongji Wu, Chao Yu, Yu Wang

Proceedings of CVPR  ·  2026CCF-A

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation

Chao Yu, Yuanqing Wang, Zhen Guo, Hao Lin, Si Xu, Hongzhi Zang, Quanlu Zhang, Yongji Wu, Chunyang Zhu, Junhao Hu, Zixiao Huang, Mingjie Wei, Yuqing Xie, Ke Yang, Bo Dai, Zhexuan Xu, Jiakun Du, Xiangyuan Wang, Xu Fu, Letong Shi, Zhihao Liu, Kang Chen, Weilin Liu, Gang Liu, Boxun Li, Jianlei Yang, Zhi Yang, Guohao Dai, Yu Wang

arXiv preprint  ·  2025

RLinf-VLA: A Unified and Efficient Framework for VLA+RL Training

Hongzhi Zang, Mingjie Wei, Si Xu, Yongji Wu, Zhen Guo, Yuanqing Wang, Hao Lin, Liangzhi Shi, Yuqing Xie, Zhexuan Xu, Zhihao Liu, Kang Chen, Wenhao Tang, Quanlu Zhang, Weinan Zhang, Chao Yu, Yu Wang

arXiv preprint  ·  2025

Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Zelai Xu, Chao Yu, Fei Fang, Yu Wang, Yi Wu

Proceedings of ICML  ·  2024CCF-A

Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Shusheng Xu, Wei Fu, Jiaxuan Gao, Wenjie Ye, Weilin Liu, Zhiyu Mei, Guangju Wang, Chao Yu, Yi Wu

Proceedings of ICML  ·  2024CCF-A

The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games

Chao Yu, Akash Velu, Eugene Vinitsky, Jiaxuan Gao, Yu Wang, Alexandre Bayen, Yi Wu

Proceedings of NeurIPS  ·  2022CCF-A

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