2 papers
cs.LG2026
Efficient Anti-exploration via VQVAE and Fuzzy Clustering in Offline Reinforcement Learning
Long Chen, Yinkui Liu, Shen Li +2
Pseudo-count is an effective anti-exploration method in offline reinforcement learning (RL) by counting state-action pairs and imposing a large penalty on rare or unseen state-acti…
cs.LG2024
DiffPoGAN: Diffusion Policies with Generative Adversarial Networks for Offline Reinforcement Learning
Xuemin Hu, Shen Li, Yingfen Xu +2
Offline reinforcement learning (RL) can learn optimal policies from pre-collected offline datasets without interacting with the environment, but the sampled actions of the agent ca…