\epsilon-Nash Mean Field Game Theory for Nonlinear Stochastic Dynamical Systems with Major and Minor Agents
Mojtaba Nourian, Peter E. Caines

TL;DR
This paper develops an $oldsymbol{ ext{ extepsilon-Nash}}$ mean field game framework for large populations of nonlinear stochastic systems with a major agent, addressing the impact of noise on mean field behavior and establishing existence, uniqueness, and equilibrium properties.
Contribution
It introduces a novel $ ext{ extepsilon-Nash}$ mean field game approach for mixed major-minor agent systems with stochastic dynamics, including solution existence and equilibrium analysis.
Findings
Established existence and uniqueness of the SMFG system solutions.
Proved $ ext{ extepsilon}_N$-Nash equilibrium property with $ ext{ extepsilon}_N=O(1/\sqrt{N})$.
Decomposed the problem into stochastic control and McKean-Vlasov equations.
Abstract
This paper studies a large population dynamic game involving nonlinear stochastic dynamical systems with agents of the following mixed types: (i) a major agent, and (ii) a population of minor agents where is very large. The major and minor (MM) agents are coupled via both: (i) their individual nonlinear stochastic dynamics, and (ii) their individual finite time horizon nonlinear cost functions. This problem is approached by the so-called -Nash Mean Field Game (-NMFG) theory. A distinct feature of the mixed agent MFG problem is that even asymptotically (as the population size approaches infinity) the noise process of the major agent causes random fluctuation of the mean field behaviour of the minor agents. To deal with this, the overall asymptotic () mean field game problem is decomposed into: (i) two non-standard stochastic optimal…
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Taxonomy
TopicsStochastic processes and financial applications · Decision-Making and Behavioral Economics · Statistical Mechanics and Entropy
