Mean Field Control and Mean Field Game Models with Several Populations
arXiv:1810.00783
Abstract
In this paper, we investigate the interaction of two populations with a large number of indistinguishable agents. The problem consists in two levels: the interaction between agents of a same population, and the interaction between the two populations. In the spirit of mean field type control (MFC) problems and mean field games (MFG), each population is approximated by a continuum of infinitesimal agents. We define four different problems in a general context and interpret them in the framework of MFC or MFG. By calculus of variations, we derive formally in each case the adjoint equations for the necessary conditions of optimality. Importantly, we find that in the case of a competition between two coalitions, one needs to rely on a system of Master equations in order to describe the equilibrium. Examples are provided, in particular linear-quadratic models for which we obtain systems of ODEs that can be related to Riccati equations.
Cited by in corpus (4)
- On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
- Systemic Risk and Heterogeneous Mean Field Type Interbank Network
- Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games
- Probabilistic Approach to Mean Field Games and Mean Field Type Control Problems with Multiple Populations