Embodied Decision Intelligence Lab (EDI Lab) 清华大学具身决策智能实验室

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.

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
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 ICLR  ·  2026CCF-A
RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
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
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
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
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
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

News

We have 12 papers accepted by ACL 2026

We have xxx papers accepted by ACL 2026: The 64th Annual Meeting of the Association for Computational Linguistics

Talks

面向具身智能的高灵活强化学习框架RLinf