Tag: offline
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Provable Offline Reinforcement Learning for Structured Cyclic MDPs
Provable Offline Reinforcement Learning for Structured Cyclic MDPs arXiv:2602.11679v1 Announce Type: new Abstract: We introduce a novel cyclic Markov decision process (MDP) framework for multi-step decision problems with heterogeneous stage-specific dynamics, transitions, and discount factors across the cycle. In this setting, offline learning is challenging: optimizing a policy at any stage shifts the state distributions…
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Operator Models for Continuous-Time Offline Reinforcement Learning
Operator Models for Continuous-Time Offline Reinforcement Learning arXiv:2511.10383v1 Announce Type: new Abstract: Continuous-time stochastic processes underlie many natural and engineered systems. In healthcare, autonomous driving, and industrial control, direct interaction with the environment is often unsafe or impractical, motivating offline reinforcement learning from historical data. However, there is limited statistical understanding of the approximation errors…