6 papers
Partially Observed Mean Field Games Without Perfect Recall: Optimality Conditions and Equilibria
Xuanping Zhang, Xiao Zhang, Wang Yao
This paper studies partially observed mean field games without perfect recall (WPR). The representative agent observes a noisy signal, but the control at time \(t\) uses only \(\ma…
Initial Error Tolerant Distributed Mean Field Control under Partial and Discrete Information
Yuxin Jin, Haotian Wang, Wang Yao +1
In this paper, an initial error tolerant distributed mean field control method under partial and discrete information is introduced, where each agent only has discrete observations…
PIONM: A Generalized Approach to Solving Density-Constrained Mean-Field Games Equilibrium under Modified Boundary Conditions
Jinwei Liu, Wang Yao, Xiao Zhang
Neural network-based methods are effective for solving equilibria in Mean-Field Games (MFGs), particularly in high-dimensional settings. However, solving the coupled partial differ…
A Constraint-Preserving Neural Network Approach for Solving Mean-Field Games Equilibrium
Jinwei Liu, Lu Ren, Wang Yao +1
Neural network-based methods have demonstrated effectiveness in solving high-dimensional Mean-Field Games (MFG) equilibria, yet ensuring mathematically consistent density-coupled e…
Linear Quadratic Mean Field Games under Heterogeneous Erroneous Initial Information
Yuxin Jin, Lu Ren, Wang Yao +1
We study a finite-horizon linear--quadratic mean field game with heterogeneous observations of the initial mean field. These observations may be erroneous and are used by agents to…
Social optimum of finite mean field games: existence and uniqueness of equilibrium solutions in the finite horizon and stationary solutions in the infinite horizon
Zijia Niu, Sanjin Huang, Lu Ren +2
In this paper, we consider the social optimal problem of discrete time finite state space mean field games (referred to as finite mean field games [1]). Unlike the individual optim…