3 papers
stat.ML2026
A Finite Sample Analysis for Quantile Temporal Difference Learning in Distributional Reinforcement Learning
Zijie Cheng, Xiang Li, Yang Peng +1
We establish a global finite-sample guarantee for synchronous quantile temporal-difference learning (QTD) in tabular distributional reinforcement learning. The proof separates two…
stat.ML2026
Online Inference for Quantile Temporal Difference Learning in Distributional Reinforcement Learning
Zijie Cheng, Yang Peng, Zhihua Zhang
In this paper, we study how to perform statistical inference for quantile temporal difference learning (QTD) in distributional reinforcement learning. Assuming access to a generati…
stat.ML2026
Statistical Efficiency and Inference of Quantile Distributional Reinforcement Learning
Zijie Cheng, Yang Peng, Zhihua Zhang
In this paper, we study quantile-based distributional reinforcement learning from the perspective of statistical efficiency. We focus on distributional policy evaluation, whose goa…