Dual Ensemble Kalman Filter for Stochastic Optimal Control

Anant A. Joshi, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn

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

Abstract

In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of reinforcement learning (RL) which is also one of our motivation. The main contribution is a simulation-based algorithm - dual ensemble Kalman filter (EnKF) - to numerically approximate the solution of these problems. The paper extends our previous work where the dual EnKF was applied in deterministic settings of the problem. The theoretical results and algorithms are illustrated with numerical experiments.

Original languageEnglish (US)
Title of host publication2024 IEEE 63rd Conference on Decision and Control, CDC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1917-1922
Number of pages6
ISBN (Electronic)9798350316339
DOIs
StatePublished - 2024
Event63rd IEEE Conference on Decision and Control, CDC 2024 - Milan, Italy
Duration: Dec 16 2024Dec 19 2024

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference63rd IEEE Conference on Decision and Control, CDC 2024
Country/TerritoryItaly
CityMilan
Period12/16/2412/19/24

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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