From the 1 of 15 linked papers with an AI index.
1 citations · 1 across the 6 of their papers we have counts for
7 papers · 1 filter
Optimality of Symmetric Independent Policies under Decentralized Mean-Field Information Sharing for Stochastic Teams and Equivalence with McKean-Vlasov Control of a Representative Agent
Sina Sanjari, Naci Saldi, Serdar Yüksel
We study a class of stochastic exchangeable teams with a finite number of decision makers (DMs) as well as their mean-field limits with infinitely many DMs. In the finite populatio…
Reinforcement Learning for Jointly Optimal Coding and Control Policies for a Controlled Markovian System over a Communication Channel
Evelyn Hubbard, Liam Cregg, Serdar Yüksel
We study the problem of joint optimization involving coding and control policies for a controlled Markovian sytem over a finite-rate noiseless communication channel. While structur…
Quantizer Design for Finite Model Approximations, Model Learning, and Quantized Q-Learning for MDPs with Unbounded Spaces
Osman Bicer, Ali D. Kara, Serdar Yuksel
In this paper, for Markov decision processes (MDPs) with unbounded state spaces we present refined upper bounds presented in [Kara et. al. JMLR'23] on finite model approximation er…
Kernel Metrics and Learning for Borel MDPs: Identifiability and Adaptive Control
Omar Mrani-Zentar, Serdar Yüksel
We consider a Markov decision process with standard Borel spaces and an unknown transition kernel under the average cost criterion. We do not impose any parametrization on the set…
Partially Observed Optimal Stochastic Control: Regularity, Optimality, Approximations, and Learning
Ali Devran Kara, Serdar Yuksel
In this review/tutorial article, we present recent progress on optimal control of partially observed Markov Decision Processes (POMDPs). We first present regularity and continuity…
Another Look at Partially Observed Optimal Stochastic Control: Existence, Ergodicity, and Approximations without Belief-Reduction
Serdar Yüksel
We present an alternative view for the study of optimal control of partially observed Markov Decision Processes (POMDPs). We first revisit the traditional (and by now standard) sep…