Local First-Order Algorithms for Constrained Nonlinear Dynamic Games

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


This paper presents algorithms for non-zero sum nonlinear constrained dynamic games with full information. Such problems emerge when multiple players with action constraints and differing objectives interact over time. They model a wide range of applications include economics, defense, and energy systems. We show how to exploit the temporal structure in projected gradient and Douglas-Rachford (DR) splitting methods. The resulting algorithms converge locally to open-loop Nash equilibria (OLNE) at linear rates. Furthermore, we extend a stagewise Newton method to find a local feedback policy around an OLNE. In the special case of linear dynamics and polyhedral constraints, we show that this local feedback controller is an approximate feedback Nash equilibrium.

Original languageEnglish (US)
Title of host publication2020 American Control Conference, ACC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538682661
StatePublished - Jul 2020
Event2020 American Control Conference, ACC 2020 - Denver, United States
Duration: Jul 1 2020Jul 3 2020

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2020 American Control Conference, ACC 2020
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2020 AACC.


Dive into the research topics of 'Local First-Order Algorithms for Constrained Nonlinear Dynamic Games'. Together they form a unique fingerprint.

Cite this