4 papers
Personalized Collaborative Learning with Affinity-Based Variance Reduction
Chenyu Zhang, Navid Azizan
Multi-agent learning faces a fundamental tension: leveraging distributed collaboration without sacrificing the personalization needed for diverse agents. This tension intensifies w…
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation
Chenyu Zhang, Xu Chen, Xuan Di
Mean field games (MFGs) model interactions in large-population multi-agent systems through population distributions. Traditional learning methods for MFGs are based on fixed-point…
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm
Fuzhong Zhou, Chenyu Zhang, Xu Chen +1
We propose a discrete time graphon game formulation on continuous state and action spaces using a representative player to study stochastic games with heterogeneous interaction amo…
A Single Online Agent Can Efficiently Learn Mean Field Games
Chenyu Zhang, Xu Chen, Xuan Di
Mean field games (MFGs) are a promising framework for modeling the behavior of large-population systems. However, solving MFGs can be challenging due to the coupling of forward pop…