10 papers
Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data
Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1
This paper addresses model-free continuous-time mean-field control in a setting where the population dynamics evolve continuously according to an unknown McKean-Vlasov stochastic d…
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…
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…