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Daniel Lacker

Researcher at Columbia University

Publications -  62
Citations -  1762

Daniel Lacker is an academic researcher from Columbia University. The author has contributed to research in topics: Uniqueness & Stochastic differential equation. The author has an hindex of 16, co-authored 58 publications receiving 1245 citations. Previous affiliations of Daniel Lacker include Brown University & Princeton University.

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Mean field games with common noise

TL;DR: In this article, a theory of existence and uniqueness for general stochastic differential mean field games with common noise is developed, and the concepts of strong and weak solutions are introduced in analogy with the theory of Stochastic Differential Equations (SDE).
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A general characterization of the mean field limit for stochastic differential games

TL;DR: In this article, the mean field limit of large-population symmetric stochastic differential games is derived in a general setting, with and without common noise, on a finite time horizon.
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A probabilistic weak formulation of mean field games and applications

TL;DR: In this article, a weak formulation of stochastic optimal control is used to study mean field games with rank and nearest-neighbor effects, where the data may depend discontinuously on the state variable and its entire history.
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A probabilistic weak formulation of mean field games and applications

TL;DR: In this paper, a weak formulation of stochastic optimal control is used to study mean field games with rank and nearest-neighbor effects, where the data may depend discontinuously on the state variable and its entire history.
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Mean field games via controlled martingale problems: Existence of Markovian equilibria

TL;DR: In this paper, the authors studied mean field games in the framework of controlled martingale problems, and general existence theorems were proven in which the equilibrium control is Markovian.