2 papers
cs.LG2026
Cross-Domain Policy Optimization via Bellman Consistency and Hybrid Critics
Ming-Hong Chen, Kuan-Chen Pan, You-De Huang +2
Cross-domain reinforcement learning (CDRL) is meant to improve the data efficiency of RL by leveraging the data samples collected from a source domain to facilitate the learning in…
cs.LG2025
Enhancing Offline Model-Based RL via Active Model Selection: A Bayesian Optimization Perspective
Yu-Wei Yang, Yun-Ming Chan, Wei Hung +2
Offline model-based reinforcement learning (MBRL) serves as a competitive framework that can learn well-performing policies solely from pre-collected data with the help of learned…