@inproceedings{1a931f54108248bfbad5a9e1a7e78cc4,
title = "Mean field social optimization: Feedback person-by-person optimality and the master equation",
abstract = "This paper considers a nonlinear mean field social optimization problem which aims to minimize a social cost. By use of a finite player model, we apply dynamic programming to formalize a person-by-person (PbP) optimality condition in a feedback form. This procedure leads to a new Hamilton-Jacobi-Bellman equation which involves differentiation with respect to probability measure and is called the master equation of social optimization. For the linear-quadratic (LQ) case, an explicit solution of the master equation is obtained.",
author = "Minyi Huang and Sheu, {Shuenn Jyi} and Sun, {Li Hsien}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 59th IEEE Conference on Decision and Control, CDC 2020 ; Conference date: 14-12-2020 Through 18-12-2020",
year = "2020",
month = dec,
day = "14",
doi = "10.1109/CDC42340.2020.9303898",
language = "???core.languages.en_GB???",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4921--4926",
booktitle = "2020 59th IEEE Conference on Decision and Control, CDC 2020",
}