4 papers
Cooperative-Competitive Team Play of Real-World Craft Robots
Rui Zhao, Xihui Li, Yizheng Zhang +6
Multi-agent deep Reinforcement Learning (RL) has made significant progress in developing intelligent game-playing agents in recent years. However, the efficient training of collect…
Human-in-the-loop Online Rejection Sampling for Robotic Manipulation
Guanxing Lu, Rui Zhao, Haitao Lin +2
Reinforcement learning (RL) is widely used to produce robust robotic manipulation policies, but fine-tuning vision-language-action (VLA) models with RL can be unstable due to inacc…
Can an Individual Manipulate the Collective Decisions of Multi-Agents?
Fengyuan Liu, Rui Zhao, Shuo Chen +4
Individual Large Language Models (LLMs) have demonstrated significant capabilities across various domains, such as healthcare and law. Recent studies also show that coordinated mul…
Efficient Preference-based Reinforcement Learning via Aligned Experience Estimation
Fengshuo Bai, Rui Zhao, Hongming Zhang +5
Preference-based reinforcement learning (PbRL) has shown impressive capabilities in training agents without reward engineering. However, a notable limitation of PbRL is its depende…