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cs.LG2026
From Suboptimal to Optimal: One-Step Latent Flow Policies for Offline Reinforcement Learning
Shenghua Lu, Zixuan Yang, Rongxu Zhao +3
Offline reinforcement learning aims to learn effective policies from fixed datasets without environment interaction. Although generative models such as diffusion and flow matching…
cs.LG2024
Transductive Reward Inference on Graph
Bohao Qu, Xiaofeng Cao, Qing Guo +3
In this study, we present a transductive inference approach on that reward information propagation graph, which enables the effective estimation of rewards for unlabelled data in o…
cs.LG2023
Policy Dispersion in Non-Markovian Environment
Bohao Qu, Xiaofeng Cao, Jielong Yang +4
Markov Decision Process (MDP) presents a mathematical framework to formulate the learning processes of agents in reinforcement learning. MDP is limited by the Markovian assumption…