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Stochastic differential mean field g...

Lacker, Daniel.

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Stochastic differential mean field game theory.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stochastic differential mean field game theory./
作者:	Lacker, Daniel.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2015,
面頁冊數:	284 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
Contained By:	Dissertation Abstracts International77-03B(E).
標題:	Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3729654
ISBN:	9781339156095

Stochastic differential mean field game theory.
Lacker, Daniel.

Stochastic differential mean field game theory. - Ann Arbor : ProQuest Dissertations & Theses, 2015 - 284 p.

Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.

Thesis (Ph.D.)--Princeton University, 2015.

Mean field game (MFG) theory generalizes classical models of interacting particle systems by replacing the particles with rational agents, making the theory more applicable in economics and other social sciences. Intuitively, (stochastic differential) MFGs are infinite-population or continuum limits of large-population stochastic differential games of a certain symmetric type, and a solution of an MFG is analogous to a Nash equilibrium. This thesis tackles several fundamental problems in MFG theory. First, if (approximate) equilibria exist in the large-population games, to what limits (if any) do they converge as the population size tends to infinity? Second, can the limiting system be used to construct approximate equilibria for the finite-population games? Finally, what can be said about existence and uniqueness of equilibria, for the finite- or infinite-population models?

ISBN: 9781339156095Subjects--Topical Terms:

515831
Mathematics.

Stochastic differential mean field game theory.
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245 1 0 $a Stochastic differential mean field game theory.
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300 $a 284 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
500 $a Adviser: Rene Carmona.
502 $a Thesis (Ph.D.)--Princeton University, 2015.
520 $a Mean field game (MFG) theory generalizes classical models of interacting particle systems by replacing the particles with rational agents, making the theory more applicable in economics and other social sciences. Intuitively, (stochastic differential) MFGs are infinite-population or continuum limits of large-population stochastic differential games of a certain symmetric type, and a solution of an MFG is analogous to a Nash equilibrium. This thesis tackles several fundamental problems in MFG theory. First, if (approximate) equilibria exist in the large-population games, to what limits (if any) do they converge as the population size tends to infinity? Second, can the limiting system be used to construct approximate equilibria for the finite-population games? Finally, what can be said about existence and uniqueness of equilibria, for the finite- or infinite-population models?
520 $a This thesis presents a complete picture of the limiting behavior of the large-population systems, both with and without common noise, under modest assumptions on the model inputs. Approximate Nash equilibria in the n-player games admit certain weak limits as n tends to infinity, and every limit is a weak solution of the MFG. Conversely, every weak MFG solution can be obtained as the limit of a sequence of approximate Nash equilibria in the n-player games. Even in the setting without common noise, a new solution concept is needed in order to capture all of the possible limits. Interestingly, and in contrast with well known results on related interacting particle systems, empirical state distributions often admit stochastic limits which are not simply randomizations among the deterministic solutions.
520 $a With the limit theory in mind, the thesis then develops new existence and uniqueness results. Using controlled martingale problems together with relaxed controls, a general existence theorem is derived by means of Kakutani's fixed point theorem. In the common noise case, a natural notion of weak solution is introduced, and the existence and uniqueness theory is designed in perfect analogy with weak solutions of stochastic differential equations. An existence theorem for weak solutions is proven by a discretization procedure, and a Yamada-Watanabe result is presented and illustrated under some stronger assumptions which ensure pathwise uniqueness.
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