Introduction to Mean Field Games and Applications

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Introduction to Mean Field Games and Applications

June 1-25, 2021

 

This program provides mathematical background for the long program in Fall 2021 on Distributed Solutions to Complex Societal Problems. Examples of the problems to be addressed in the long program include modeling phenomena such as the macroeconomy, conflict, financial regulation, crowd movement, big data, and advertising, as well as engineering problems involving decentralized intelligence, machine learning, and telecommunications.

An important mathematical development contributing to the understanding of such problems is the theory of Mean Field Games. This is a mathematical framework well-suited to
the study of models in which a large number of agents interact strategically in a stochastically evolving environment, all responding to a range of incentives,
and all trying to simultaneously forecast the decisions of other agents.

Introduction to Decision Making and Uncertainty

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Introduction to Decision Making and Uncertainty

Jun 28-July 23, 2021

 

How do we make decisions in the face of risk? The need to make decisions in the presence of uncertainty cuts across a wide range of issues in science and human behavior. The underlying problems require both sophisticated modeling and advanced mathematical and statistical approaches and techniques.

This program will serve as an introduction to the long program on Decision Making and Uncertainty scheduled for Spring 2022. It aims to introduce participants to a variety of modeling questions and methods of current interest in this area. It will be built on “thematic clusters” of emerging areas of application.