Asymptotic Analysis of Sample-Averaged Q-Learning

Reinforcement learning (RL) has emerged as a key approach for training agents in complex and uncertain environments. Incorporating statistical inference in RL algorithms is essential for understanding and managing uncertainty in model performance. This paper introduces a generalized framework for ti...

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Bibliographic Details

Published in:	IEEE transactions on information theory Vol. 71; no. 7; pp. 5601 - 5619
Main Authors:	Panda, Saunak Kumar, Liu, Ruiqi, Xiang, Yisha
Format:	Journal Article
Language:	English
Published:	IEEE 01.07.2025
Subjects:	Accuracy Approximation algorithms asymptotic normality Convergence Estimation Inference algorithms Q-learning random scaling Reinforcement learning (RL) Reliability statistical inference Stochastic processes Training Uncertainty
ISSN:	0018-9448, 1557-9654
Online Access:	Get full text
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