Controlled interacting particle algorithms for simulation-based reinforcement learning-Reference-Cited by-同舟云学术

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Controlled interacting particle algorithms for simulation-based reinforcement learning

Published:2022-12 Issue: Volume:170 Page:105392
ISSN:0167-6911
Container-title:Systems & Control Letters
language:en
Short-container-title:Systems & Control Letters

Author:

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

Funder

National Science Foundation Directorate for Engineering

National Science Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,General Computer Science,Control and Systems Engineering

Reference67 articles.

1. Mastering atari, go, chess and shogi by planning with a learned model;Schrittwieser;Nature,2020

2. Data Assimilation. The Ensemble Kalman Filter;Evensen,2006

3. Probabilistic Forecasting and Bayesian Data Assimilation;Reich,2015

4. Contributions to the theory of optimal control;Kalman;Boletin de la Soc. Mat. Mexicana,1960

5. Algebraic Riccati Equations;Lancaster,1995

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1. Convex Q Learning in a Stochastic Environment;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

2. A survey of feedback particle filter and related controlled interacting particle systems (CIPS);Annual Reviews in Control;2023

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