Nian Si

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20242026

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math.OC2026

Non-Rectangular Average-Reward Robust MDPs: Optimal Policies and Their Transient Values

Shengbo Wang, Nian Si

We study non-rectangular robust Markov decision processes under the average-reward criterion, where the ambiguity set couples transition probabilities across states and the adversa…

cs.LG2026

Achieving $ε^{- 2}$ Dependence for Average-Reward Q-Learning with a New Contraction Principle

Zijun Chen, Zaiwei Chen, Nian Si +1

We present the convergence rates of synchronous and asynchronous Q-learning for average-reward Markov decision processes, where the absence of contraction poses a fundamental chall…

Non-Rectangular Average-Reward Robust MDPs: Optimal Policies and Their Transient Values

Achieving ε−2 Dependence for Average-Reward Q-Learning with a New Contraction Principle

Achieving $ε^{- 2}$ Dependence for Average-Reward Q-Learning with a New Contraction Principle