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cs.RO2025
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio +4
Policy learning under action constraints plays a central role in ensuring safe behaviors in various robot control and resource allocation applications. In this paper, we study a ne…
cs.LG2025
Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
Wei Hung, Shao-Hua Sun, Ping-Chun Hsieh
Action-constrained reinforcement learning (ACRL) is a generic framework for learning control policies with zero action constraint violation, which is required by various safety-cri…
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…