Offline Constrained Reinforcement Learning under Partial Data Coverage
arXiv:2505.17506v2 Announce Type: replace
Abstract: We study offline constrained reinforcement learning with general function approximation in discounted constrained Markov decision processes. Prior methods either require full data coverage for evalua…