PT - Journal Article
AU - Chen, Yongxin
AU - Georgiou, Tryphon T.
AU - Pavon, Michele
DP - 2021
TI - Optimal Transport in Systems and Control
TA - Annual Review of Control, Robotics, and Autonomous Systems,
VI - 4
IP - Volume 4, 2021
PG - 89-113
AID - 10.1146/annurev-control-070220-100858
SO - Annual Review of Control, Robotics, and Autonomous Systems 2021;4(1):89-113
AB - Optimal transport began as the problem of how to efficiently redistribute goods between production and consumers and evolved into a far-reaching geometric variational framework for studying flows of distributions on metric spaces. This theory enables a class of stochastic control problems to regulate dynamical systems so as to limit uncertainty to within specified limits. Representative control examples include the landing of a spacecraft aimed probabilistically toward a target and the suppression of undesirable effects of thermal noise on resonators; in both of these examples, the goal is to regulate the flow of the distribution of the random state. A most unlikely link turned up between transport of probability distributions and a maximum entropy inference problem posed by Erwin SchrÃ¶dinger, where the latter is seen as an entropy-regularized version of the former. These intertwined topics of optimal transport, stochastic control, and inference are the subject of this review, which aims to highlight connections, insights, and computational tools while touching on quadratic regulator theory and probabilistic flows in discrete spaces and networks.,
4099- https://www.annualreviews.org
4100- https://www.annualreviews.org/content/journals/10.1146/annurev-control-070220-100858