8 citations · 12 across the 7 of their papers we have counts for
8 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…
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…
Kernel Based Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games
Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi
We consider the maximum causal entropy inverse reinforcement learning (IRL) problem for infinite-horizon stationary mean-field games (MFG), in which we model the unknown reward fun…
Maximum Causal Entropy IRL in Mean-Field Games and GNEP Framework for Forward RL
Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi
This paper explores the use of Maximum Causal Entropy Inverse Reinforcement Learning (IRL) within the context of discrete-time stationary Mean-Field Games (MFGs) characterized by f…
Q-Learning in Regularized Mean-field Games
Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi
In this paper, we introduce a regularized mean-field game and study learning of this game under an infinite-horizon discounted reward function. Regularization is introduced by addi…
Learning in Discounted-cost and Average-cost Mean-field Games
Berkay Anahtarcı, Can Deha Karıksız, Naci Saldi
We consider learning approximate Nash equilibria for discrete-time mean-field games with nonlinear stochastic state dynamics subject to both average and discounted costs. To this e…
Value Iteration Algorithm for Mean-field Games
Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi
In the literature, existence of mean-field equilibria has been established for discrete-time mean field games under both the discounted cost and the average cost optimality criteri…
Non-signaling Approximations of Stochastic Team Problems
Naci Saldi, Can Deha Karıksız, Maxim Raginsky +1
In this paper, we consider non-signaling approximation of finite stochastic teams. We first introduce a hierarchy of team decision rules that can be classified in an increasing ord…