Functional role of synchronization: A mean-field control perspective

TL;DR

This paper surveys mean-field control methods to understand and influence the collective behavior of interconnected dynamical systems across various fields, focusing on controlled coupled oscillators.

Contribution

It provides a comprehensive overview of mean-field game approaches applied to controlled coupled oscillators, highlighting their potential in predicting and controlling emergent phenomena.

Findings

Mean-field models effectively predict collective behavior.

Distributed control schemes can influence system dynamics.

Survey highlights applications in neuroscience, physics, and economics.

Abstract

The broad goal of the research surveyed in this article is to develop methods for understanding the aggregate behavior of interconnected dynamical systems, as found in mathematical physics, neuroscience, economics, power systems and neural networks. Questions concern prediction of emergent (often unanticipated) phenomena, methods to formulate distributed control schemes to influence this behavior, and these topics prompt many other questions in the domain of learning. The area of mean field games, pioneered by Peter Caines, are well suited to addressing these topics. The approach is surveyed in the present paper within the context of controlled coupled oscillators.