59 citations · 164 across the 56 of their papers we have counts for
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Kernel Mean Embedding Topology: Weak and Strong Forms for Stochastic Kernels and Implications for Model Learning
Naci Saldi, Serdar Yuksel
We introduce a novel topology, called Kernel Mean Embedding Topology, for stochastic kernels, in a weak and strong form. This topology, defined on the spaces of Bochner integrable…
Robustness to Model Approximation, Model Learning From Data, and Sample Complexity in Wasserstein Regular MDPs
Yichen Zhou, Yanglei Song, Serdar Yüksel
The paper studies the robustness properties of discrete-time stochastic optimal control under Wasserstein model approximation for both discounted-cost and average-cost criteria. Sp…
Robustness to Incorrect Models and Data-Driven Learning in Average-Cost Optimal Stochastic Control
Ali Devran Kara, Maxim Raginsky, Serdar Yuksel
We study continuity and robustness properties of infinite-horizon average expected cost problems with respect to (controlled) transition kernels, and applications of these results…
Robustness to incorrect system models in stochastic control
Ali Devran Kara, Serdar Yüksel
In stochastic control applications, typically only an ideal model (controlled transition kernel) is assumed and the control design is based on the given model, raising the problem…
Robustness to incorrect priors in partially observed stochastic control
Ali Devran Kara, Serdar Yüksel
We study the continuity properties of optimal solutions to stochastic control problems with respect to initial probability measures and applications of these to the robustness of o…
Finite Model Approximations for Partially Observed Markov Decision Processes with Discounted Cost
Naci Saldi, Serdar Yüksel, Tamás Linder
We consider finite model approximations of discrete-time partially observed Markov decision processes (POMDPs) under the discounted cost criterion. After converting the original pa…