67 citations · 227 across the 41 of their papers we have counts for
32 papers · 1 filter
Approximations and Learning for Decentralized Stochastic Control and Near Optimal Finite Window Policies
Omar Mrani-Zentar, Serdar Yuksel
Decentralized stochastic control problems are difficult to study due to information structure dependent subtleties, which prevent many classical methods in stochastic control from…
Mean-Field Systems with Heterogeneous Subteams: Optimality of Cluster-Symmetric Independent Policies and Equivalence with Decentralized McKean-Vlasov Control of Cluster-Representative Agents
Connor S. Braun, Sina Sanjari, Naci Saldi +2
Across science and engineering, mean-field methods have been a powerful and versatile approach for the analysis of systems of many interacting elements. However, common arguments u…
Reinforcement Learning for Discounted and Ergodic Control of Diffusion Processes
Erhan Bayraktar, Ali D. Kara, Somnath Pradhan +1
This paper develops a quantized Q-learning algorithm for the optimal control of controlled diffusion processes on under both discounted and ergodic (average) cost cr…
Near Optimality of Discrete-Time Approximations for Controlled McKean-Vlasov and Large Interacting Particle Diffusions
Somnath Pradhan, Serdar Yuksel
We study stochastic optimal control problems for (possibly degenerate) McKean-Vlasov controlled diffusions and obtain discrete-time as well as finite interacting particle approxima…
Sensitivity of Filter Kernels and Robustness Bounds to Transition and Measurement Kernel Perturbations in Partially Observable Stochastic Control
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
Studying the stability of partially observed Markov decision processes (POMDPs) with respect to perturbations in either transition or observation kernels is a significant problem.…
Discrete-Time Approximations of Controlled Diffusions with Infinite Horizon Discounted and Average Cost
Somnath Pradhan, Serdar Yuksel
We present discrete-time approximation of optimal control policies for infinite horizon discounted/ergodic control problems for controlled diffusions in $\Rd$\,. In particular, our…
Near Optimal Approximations and Finite Memory Policies for POMPDs with Continuous Spaces
Ali Devran Kara, Erhan Bayraktar, Serdar Yuksel
We study an approximation method for partially observed Markov decision processes (POMDPs) with continuous spaces. Belief MDP reduction, which has been the standard approach to stu…
Refined Bounds on Near Optimality Finite Window Policies in POMDPs and Their Reinforcement Learning
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
Finding optimal policies for Partially Observable Markov Decision Processes (POMDPs) is challenging due to their uncountable state spaces when transformed into fully observable Mar…
Centralized Reduction of Decentralized Stochastic Control Models and their weak-Feller Regularity
Omar Mrani-Zentar, Serdar Yüksel
Decentralized stochastic control problems involving general state/measurement/action spaces are intrinsically difficult to study because of the inapplicability of standard tools fr…
Near Optimality of Lipschitz and Smooth Policies in Controlled Diffusions
Somnath Pradhan, Serdar Yuksel
For optimal control of diffusions under several criteria, due to computational or analytical reasons, many studies have a apriori assumed control policies to be Lipschitz or smooth…
Decentralized Exchangeable Stochastic Dynamic Teams in Continuous-time, their Mean-Field Limits and Optimality of Symmetric Policies
Sina Sanjari, Naci Saldi, Serdar Yüksel
We study a class of stochastic exchangeable teams comprising a finite number of decision makers (DMs) as well as their mean-field limits involving infinite numbers of DMs. In the f…
Subjective Equilibria under Beliefs of Exogenous Uncertainty: Linear Quadratic Case
Gürdal Arslan, Serdar Yüksel
We consider a stochastic dynamic game where players have their own linear state dynamics and quadratic cost functions. Players are coupled through some environment variables, gener…
Average Cost Optimality of Partially Observed MDPS: Contraction of Non-linear Filters, Optimal Solutions and Approximations
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
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 measur…
Controlled Diffusions under Full, Partial and Decentralized Information: Existence of Optimal Policies and Discrete-Time Approximations
Somnath Pradhan, Serdar Yüksel
We present existence and discrete-time approximation results on optimal control policies for continuous-time stochastic control problems under a variety of information structures.…
Robustness of Optimal Controlled Diffusions with Near-Brownian Noise via Rough Paths Theory
Somnath Pradhan, Zachary Selk, Serdar Yüksel
In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idea…
Sliding Window Codes: Near-Optimality and Q-Learning for Zero-Delay Coding
Liam Cregg, Fady Alajaji, Serdar Yuksel
We study the problem of zero-delay coding for the transmission of a Markov source over a noisy channel with feedback and present a reinforcement learning solution which is guarante…
Approximations and Learning for Continuous State and Action MDPs under Average Cost Criteria
Ali Devran Kara, Serdar Yuksel
In this paper, for Markov Decision Processes (MDPs) with standard Borel spaces, (i) we first provide a discretization based approximation method for MDPs with continuous spaces und…
Nash Equilibria for Exchangeable Team against Team Games, their Mean Field Limit, and Role of Common Randomness
Sina Sanjari, Naci Saldi, Serdar Yüksel
We study stochastic mean-field games among finite number of teams with large finite as well as infinite number of decision makers. For this class of games within static and dynamic…
Non-Sequential Decentralized Stochastic Control Revisited: Causality and Static Reducibility
Omar Mrani-Zentar, Ryan Simpson, Serdar Yüksel
In decentralized stochastic control (or stochastic team theory) and game theory, if there is a pre-defined order in a system in which agents act, the system is called \textit{seque…
Continuity of Cost in Borkar Control Topology and Implications on Discrete Space and Time Approximations for Controlled Diffusions under Several Criteria
Somnath Pradhan, Serdar Yüksel
We first show that the discounted cost, cost up to an exit time, and ergodic cost involving controlled non-degenerate diffusions are continuous on the space of stationary control p…
Robustness of Stochastic Optimal Control to Approximate Diffusion Models under Several Cost Evaluation Criteria
Somnath Pradhan, Serdar Yuksel
In control theory, typically a nominal model is assumed based on which an optimal control is designed and then applied to an actual (true) system. This gives rise to the problem of…
Isomorphism Properties of Optimality and Equilibrium Solutions under Equivalent Information Structure Transformations: Stochastic Dynamic Games and Teams
Sina Sanjari, Tamer Başar, Serdar Yüksel
Static reduction of information structures (ISs) is a method that is commonly adopted in stochastic control, team theory, and game theory. One approach entails change of measure ar…
Isomorphism Properties of Optimality and Equilibrium Solutions under Equivalent Information Structure Transformations I: Stochastic Dynamic Teams
Sina Sanjari, Tamer Başar, Serdar Yüksel
In stochastic optimal control, change of measure arguments have been crucial for stochastic analysis. Such an approach is often called static reduction in dynamic team theory (or d…
Geometry of Information Structures, Strategic Measures and associated Control Topologies
Naci Saldi, Serdar Yuksel
In many areas of applied mathematics, engineering, and social and natural sciences, decentralization of information is a key aspect determining how to approach a problem. In this r…