3 papers
cs.LG2024
Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
Jing Zhang, Linjiajie Fang, Kexin Shi +2
``Distribution shift'' is the main obstacle to the success of offline reinforcement learning. A learning policy may take actions beyond the behavior policy's knowledge, referred to…
cs.LG2024
Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning
Linjiajie Fang, Ruoxue Liu, Jing Zhang +2
In offline reinforcement learning, it is necessary to manage out-of-distribution actions to prevent overestimation of value functions. One class of methods, the policy-regularized…
cs.LG2023
Constrained Policy Optimization with Explicit Behavior Density for Offline Reinforcement Learning
Jing Zhang, Chi Zhang, Wenjia Wang +1
Due to the inability to interact with the environment, offline reinforcement learning (RL) methods face the challenge of estimating the Out-of-Distribution (OOD) points. Existing m…