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T. Başar

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Preprint Sep 2026

Infinite Horizon Mean-Field Terminal Value Problem

We introduce a class of finite- and infinite-horizon discrete-time control problems for studying macroscale systems in discrete time, which we refer to as mean-field terminal value problems (MFTVPs). An MFTVP takes a terminal \(Q\)-function as input and, starting from this terminal \(Q\)-function, seeks an indefinite b...

U. Aydın, T. Başar, Naci Saldi · 0 citations
#machine learning Preprint Sep 2026

Conditioning Degenerate Diffusion Models

This work uses causal optimal transport to define loss functions that identify a minimum-entropy control for guidance under minimal assumptions in conditioned generative models.

U. Aydın, T. Başar · 0 citations
Preprint Aug 2026

Monotone Inclusion Approach to Weakly Monotone Discrete-Time Finite-Horizon Mean-Field Games

We revisit the problem of computing mean-field equilibria (MFEs) in discrete-time, monotone, finite-horizon mean-field games (MFGs). We show that, when the transition kernel is independent of the state-measure term and the reward function satisfies the usual weak monotonicity condition and is Lipschitz continuous, anch...

U. Aydın, T. Başar, Naci Saldi · 0 citations
Preprint Aug 2026

Horizon-Independent Contraction for Continuous-Time Discounted Regularized Mean-Field Games

We study contraction properties of non-stationary continuous-time mean-field games (MFGs) under discounting and entropy regularization. The state of the representative agent evolves according to a controlled continuous-time Markov chain, and both the state and action spaces are finite. In contrast to the undiscounted c...

Jun-Ji Yan, U. Aydın, T. Başar · 0 citations

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