25 citations · 71 across the 36 of their papers we have counts for
47 papers
Entropy-Regularized Mean-Field Games with Average-Reward Criterion: Span-Seminorm Contractions and Model-Free Learning
Gunes Akbas, Naci Saldi, Berkay Anahtarci +1
We study stationary discrete-time mean-field games with finite state and action spaces under the average-reward criterion, with an entropy-regularized objective and population-depe…
Infinite Horizon Mean-Field Terminal Value Problem
Uğur Aydın, Tamer Başar, Naci Saldi
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…
Monotone Inclusion Approach to Weakly Monotone Discrete-Time Finite-Horizon Mean-Field Games
Uğur Aydın, Tamer Başar, Naci Saldi
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 ind…
Generalization Bounds on Optimal Control for Transformer Training and Wasserstein Distributional Robustness
Kağan Akman, Naci Saldi, Serdar Yüksel
We derive finite-sample generalization bounds for Transformers trained with dynamic programming recursions. Building on the doubly lifted, measure-valued formulation of Transformer…
Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games with Average Reward
Şevket Kaan Alkır, Naci Saldı, Berkay Anahtarcı +1
We study inverse reinforcement learning for discrete-time, infinite-horizon mean-field games (MFGs) under an average-reward criterion. Expert demonstrations are assumed to arise fr…
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…