3 papers
math.OC2025
Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces
Andrea Angiuli, Jean-Pierre Fouque, Ruimeng Hu +1
We present the development and analysis of a reinforcement learning (RL) algorithm designed to solve continuous-space mean field game (MFG) and mean field control (MFC) problems in…
math.OC2024
Analysis of Multiscale Reinforcement Q-Learning Algorithms for Mean Field Control Games
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière +1
Mean Field Control Games (MFCG), introduced in [Angiuli et al., 2022a], represent competitive games between a large number of large collaborative groups of agents in the infinite l…
math.OC2024
Convergence of Multi-Scale Reinforcement Q-Learning Algorithms for Mean Field Game and Control Problems
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière +1
We establish the convergence of the unified two-timescale Reinforcement Learning (RL) algorithm presented in a previous work by Angiuli et al. This algorithm provides solutions to…