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A Finite Sample Analysis for Quantile Temporal Difference Learning in Distributional Reinforcement Learning

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We establish a global finite-sample guarantee for synchronous quantile temporal-difference learning (QTD) in tabular distributional reinforcement learning. The proof separates two stability mechanisms.

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reinforcement-learning

arXiv Machine Learning

Aug 28

A Finite Sample Analysis for Quantile Temporal Difference Learning in Distributional Reinforcement Learning

arXiv:2608. 27313v1 Announce Type: cross Abstract: We establish a global finite-sample guarantee for synchronous quantile temporal-difference learning (QTD) in tabular distributional reinforcement learning.

By Zijie Cheng, Xiang Li, Yang Peng, Zhihua Zhang

reinforcement-learning

arXiv Machine Learning

Sep 18

A Finite-Sample Analysis of Quantile Temporal-Difference Learning

arXiv:2608. 27313v2 Announce Type: replace-cross Abstract: Quantile temporal-difference learning (QTD) is an effective method for learning return distributions through quantile approximation, yet its finite-time behavior remains poorly understood.

By Zijie Cheng, Xiang Li, Yang Peng, Zhihua Zhang

arXiv Machine Learning

2d ago

Online Inference for Quantile Distributional Reinforcement Learning

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By Zijie Cheng, Yang Peng, Zhihua Zhang

reinforcement-learning

arXiv Machine Learning

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Steady-State Convergence of Stochastic Approximation

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By Yixuan Zhang, Qiaomin Xie

reinforcement-learning safety

arXiv Machine Learning

Aug 14

Online Inference for Quantile Temporal Difference Learning in Distributional Reinforcement Learning

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By Zijie Cheng, Yang Peng, Zhihua Zhang

reinforcement-learning

arXiv Machine Learning

Oct 12

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By Yang Peng

reinforcement-learning

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