4 papers
Functional Critics Are Essential for Actor-Critic: From Off-Policy Stability to Efficient Exploration
Qinxun Bai, Yuxuan Han, Wei Xu +1
The actor-critic (AC) framework has achieved strong empirical success in off-policy reinforcement learning but suffers from the "moving target" problem, where the evaluated policy…
Learning Multi-Stage Pick-and-Place with a Legged Mobile Manipulator
Haichao Zhang, Haonan Yu, Le Zhao +4
Quadruped-based mobile manipulation presents significant challenges in robotics due to the diversity of required skills, the extended task horizon, and partial observability. After…
Concurrent Learning with Aggregated States via Randomized Least Squares Value Iteration
Yan Chen, Qinxun Bai, Yiteng Zhang +4
Designing learning agents that explore efficiently in a complex environment has been widely recognized as a fundamental challenge in reinforcement learning. While a number of works…
SLIM: Sim-to-Real Legged Instructive Manipulation via Long-Horizon Visuomotor Learning
Haichao Zhang, Haonan Yu, Le Zhao +4
We present a low-cost legged mobile manipulation system that solves long-horizon real-world tasks, trained by reinforcement learning purely in simulation. This system is made possi…