177 citations · 290 across the 29 of their papers we have counts for
8 papers · 1 filter
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments
Jinyi Liu, Zhi Wang, Yan Zheng +6
In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream principle for directing exploration towards less explored areas, characterized by higher un…
Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness
Xiaoyu Wen, Xudong Yu, Rui Yang +3
To obtain a near-optimal policy with fewer interactions in Reinforcement Learning (RL), a promising approach involves the combination of offline RL, which enhances sample efficienc…
Robust Quadrupedal Locomotion via Risk-Averse Policy Learning
Jiyuan Shi, Chenjia Bai, Haoran He +6
The robustness of legged locomotion is crucial for quadrupedal robots in challenging terrains. Recently, Reinforcement Learning (RL) has shown promising results in legged locomotio…
On the Value of Myopic Behavior in Policy Reuse
Kang Xu, Chenjia Bai, Shuang Qiu +5
Leveraging learned strategies in unfamiliar scenarios is fundamental to human intelligence. In reinforcement learning, rationally reusing the policies acquired from other tasks or…
Behavior Contrastive Learning for Unsupervised Skill Discovery
Rushuai Yang, Chenjia Bai, Hongyi Guo +5
In reinforcement learning, unsupervised skill discovery aims to learn diverse skills without extrinsic rewards. Previous methods discover skills by maximizing the mutual informatio…
Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective
Haoran He, Peilin Wu, Chenjia Bai +5
Reinforcement Learning (RL) has recently achieved remarkable success in robotic control. However, most works in RL operate in simulated environments where privileged knowledge (e.g…
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning
Haoran He, Chenjia Bai, Kang Xu +5
Diffusion models have demonstrated highly-expressive generative capabilities in vision and NLP. Recent studies in reinforcement learning (RL) have shown that diffusion models are a…
Cross-Domain Policy Adaptation via Value-Guided Data Filtering
Kang Xu, Chenjia Bai, Xiaoteng Ma +5
Generalizing policies across different domains with dynamics mismatch poses a significant challenge in reinforcement learning. For example, a robot learns the policy in a simulator…