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math.OC2026
The Complexity of Approximating the Value in Revealing POMDPs with Long-Run Average Objectives
Ali Asadi, Krishnendu Chatterjee, David Lurie
We study partially observable Markov decision processes (POMDPs) with long-run average objectives, where the payoff is defined as the limit inferior of the expected average rewards…
math.OC2026
Approximating the Uniform Value in Hidden Stochastic Games with Doeblin Condition
Krishnendu Chatterjee, David Lurie, Raimundo Saona +1
We study \emph{zero-sum two-player hidden stochastic games}, where players receive partial observations of the state. We focus on a central solution concept for analyzing long-dura…