12 papers
Mean-Field Control with a Common Hidden State under Decentralized Observations
Erhan Bayraktar, Ali D. Kara
We study optimal control of a system with multiple decision makers who share a common hidden state and receive fully decentralized observations through identical channels. The dyna…
Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data
Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1
This paper develops a model-free framework for continuous-time mean-field control when the population evolves according to unknown controlled McKean--Vlasov dynamics and only discr…
Equilibrium for Time-inconsistent Mean Field Games: A Systematic Analysis by Entropy Regularization
Erhan Bayraktar, Zhenhua Wang, Xiang Yu +1
This paper studies the existence and approximation of equilibria for general time-inconsistent mean field game (MFG) problems in continuous time. To handle the intricate nonlocal e…
Policy Gradient for Continuous-Time Mean-Field Control
Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1
This paper develops a policy gradient method for entropy-regularized mean-field control in the discounted infinite-horizon setting. We consider randomized feedback policies and a c…
Analytical Approach to Continuous-Time Causal Optimal Transport
Julio Backhoff, Erhan Bayraktar, Ibrahim Ekren +1
We study causal optimal transport in continuous time, with Markovian cost, between a finite-state Markov source and a diffusion target. By replacing the source with its conditional…
Continuous-time Online Learning via Mean-Field Neural Networks: Regret Analysis in Diffusion Environments
Erhan Bayraktar, Bingyan Han, Ziqing Zhang
We study continuous-time online learning where data are generated by a diffusion process with unknown coefficients. The learner employs a two-layer neural network, continuously upd…
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 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…
Learning with Linear Function Approximations in Mean-Field Control
Erhan Bayraktar, Ali D. Kara
The paper focuses on mean-field type multi-agent control problems with finite state and action spaces where the dynamics and cost structures are symmetric and homogeneous, and are…
Binomial-tree approximation for time-inconsistent stopping
Erhan Bayraktar, Zhenhua Wang, Zhou Zhou
For time-inconsistent stopping in a one-dimensional diffusion setup, we investigate how to use discrete-time models to approximate the original problem. In particular, we consider…
On Time-Inconsistency in Mean Field Games
Erhan Bayraktar, Zhenhua Wang
We investigate an infinite-horizon time-inconsistent mean-field game (MFG) in a discrete time setting. We first present a classic equilibrium for the MFG and its associated existen…
Infinite Horizon Average Cost Optimality Criteria for Mean-Field Control
Erhan Bayraktar, Ali D. Kara
We study mean-field control problems in discrete-time under the infinite horizon average cost optimality criteria. We focus on both the finite population and the infinite populatio…