Reinforcement Learning

ReDMan: Reliable Dexterous Manipulation with Safe Reinforcement Learning

Dexterous hand manipulation is a crucial ability for robots in various applications. However, ensuring safety and reliability during …

Yiran Geng, Jiaming Ji, Yuanpei Chen, Haoran Geng, Fangwei Zhong, Yaodong Yang

Remember the Past for Better Future: Memory-Augmented Offline RL

As a foundation of human intelligence, memory has been found to be critical for human attention and decision making. However, it is …

Yue Zhang, Yaodong Yang, Zhenbo Lu, Wengang Zhou, Houqiang Li

Grasp Multiple Objects with One Hand

The intricate kinematics of the human hand enable simultaneous grasping and manipulation of multiple objects, essential for tasks, such …

Yuyang Li, Bo Liu, Yiran Geng, Puhao Li, Yaodong Yang, Yixin Zhu, Tengyu Liu, Siyuan Huang

GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models

This paper introduces a distributed, GPU-centric experience replay system, GEAR, designed to perform scalable reinforcement learning …

Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai

A Deep Reinforcement Learning-driven Vine Copula Method for Correlation Structure Analysis of Mortgage

Controlling risk is the key to playing a core role in financial services and effectively serving the high-quality development of the …

Qinghao Wang, Yanling PENG, Yijie Peng, Yaodong Yang

Learning to Shape Rewards using a Game of Two Partners

Reward shaping (RS) is a powerful method in reinforcement learning (RL) for overcoming the problem of sparse or uninformative rewards. …

David Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Tianpei Yang, Matthew Taylor, Wenbin Song, Feifei Tong, Hui Chen, Jiangcheng Zhu, Jun Wang, Yaodong Yang

Quality-Similar Diversity via Population Based Reinforcement Learning

Diversity is a growing research topic in Reinforcement Learning (RL). Previous research on diversity has mainly focused on promoting …

Shuang Wu, Jian Yao, Haobo Fu, Ye Tian, Chao Qian, Yaodong Yang, QIANG FU, Yang Wei

Solving Inventory Management Problems through Deep Reinforcement Learning

Inventory management (e.g. lost sales) is a central problem in supply chain management. Lost sales inventory systems with lead times …

Qinghao Wang, Yijie Peng, Yaodong Yang

MSRL: Distributed Reinforcement Learning with Dataflow Fragments

Reinforcement learning (RL) trains many agents, which is resource-intensive and must scale to large GPU clusters. Different RL training …

Huanzhou Zhu, Bo Zhao, Gang Chen, Weifeng Chen, Yijie Chen, Liang Shi, Yaodong Yang, Peter Pietzuch, Lei Chen