Q-learning in regularized mean-field games
In this paper, we introduce a regularized mean-field game and study learning of this game
under an infinite-horizon discounted reward function. Regularization is introduced by adding …
under an infinite-horizon discounted reward function. Regularization is introduced by adding …
Average Cost Optimality of Partially Observed MDPs: Contraction of Nonlinear Filters and Existence of Optimal Solutions and Approximations
The average cost optimality is known to be a challenging problem for partially observable
stochastic control, with few results available beyond the finite state, action, and …
stochastic control, with few results available beyond the finite state, action, and …
On Borkar and Young relaxed control topologies and continuous dependence of invariant measures on control policy
S Yüksel - SIAM Journal on Control and Optimization, 2024 - SIAM
In deterministic and stochastic control theory, relaxed or randomized control policies allow
for versatile mathematical analysis (on continuity, compactness, convexity, and …
for versatile mathematical analysis (on continuity, compactness, convexity, and …
Partially Observed Optimal Stochastic Control: Regularity, Optimality, Approximations, and Learning
AD Kara, S Yuksel - arXiv preprint arXiv:2412.06735, 2024 - arxiv.org
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 …
observed Markov Decision Processes (POMDPs). We first present regularity and continuity …
Robustness to incorrect priors and controlled filter stability in partially observed stochastic control
C McDonald, S Yüksel - SIAM Journal on Control and Optimization, 2022 - SIAM
We study controlled filter stability and its effects on the robustness properties of optimal
control policies designed for systems with incorrect priors applied to a true system. Filter …
control policies designed for systems with incorrect priors applied to a true system. Filter …
Robustness to incorrect system models in stochastic control
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 of …
is assumed and the control design is based on the given model, raising the problem of …
Robustness and Approximation of Discrete-time Mean-field Games under Discounted Cost Criterion
In this paper, we investigate the robustness of stationary mean-field equilibria in the
presence of model uncertainties, specifically focusing on infinite-horizon discounted cost …
presence of model uncertainties, specifically focusing on infinite-horizon discounted cost …
Continuity properties of value functions in information structures for zero-sum and general games and stochastic teams
I Hogeboom-Burr, S Yüksel - SIAM Journal on Control and Optimization, 2023 - SIAM
We study continuity properties of stochastic game problems with respect to various
topologies on information structures, defined as probability measures characterizing a …
topologies on information structures, defined as probability measures characterizing a …
Signaling-based Robust Incentive Designs with Randomized Monitoring
Incentive design problems entail hierarchical decision-making where a leader crafts a
strategy to induce a desired response from a follower. Such dynamic games with …
strategy to induce a desired response from a follower. Such dynamic games with …
Robustness to approximations and model learning in MDPs and POMDPs
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 of …
is assumed and the control design is based on the given model, raising the problem of …