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Mean field game theory : ウィキペディア英語版
Mean field game theory
Mean field game theory is the study of strategic decision making in very large populations of small interacting individuals. This
class of problems was considered in the economics literature by Jovanovic and Rosenthal,〔Jovanovic, Boyan and Rosenthal, Robert W., 1988. "Anonymous sequential games," Journal of Mathematical Economics, Elsevier, vol. 17(1), pages 77–87, February〕 in the engineering literature by Peter E. Caines and his co-workers〔M.Y. Huang, R.P. Malhame and P.E. Caines, "Large Population
Stochastic Dynamic Games: Closed-Loop McKean–Vlasov Systems and
the Nash Certainty Equivalence Principle," Special issue in honor of
the 65th birthday of Tyrone Duncan,Communications in Information and
Systems. Vol 6, Number 3, 2006, pp 221–252.〕〔M. Nourian and P. E. Caines, "–Nash mean field game theory for nonlinear stochastic dynamical systems with major and minor agents," SIAM Journal on Control and Optimization, Vol. 51, No. 4, 2013, pp. 3302–3331.〕
and independently and around the same time by Jean-Michel Lasry and Pierre-Louis Lions.
Use of the term 'mean field' is inspired by mean field theory in physics which considers the behaviour of systems of large numbers of particles where individual particles have negligible impact upon the system.
==See also==

* Aggregative game

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