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Chenbei Lu

2 accepted papers

2025

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

ICML 2025poster

Factored Markov Decision Processes (FMDPs) offer a promising framework for overcoming the curse of dimensionality in reinforcement learning (RL) by decomposing high-dimensional MDPs into smaller and independently evolving components. Despite their potential, existing studies on FMDPs face three key…

Cited by 1SourcePDFScholar
2025

Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach

NeurIPS 2025spotlight

Traditional reinforcement learning (RL) assumes the agents make decisions based on Markov decision processes (MDPs) with one-step transition models. In many real-world applications, such as energy management and stock investment, agents can access multi-step predictions of future states, which provi…

Cited by 0SourceScholar