Toward Data-Driven Optimal Control: A Systematic Review of the Landscape-Reference-Cited by-同舟云学术

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Toward Data-Driven Optimal Control: A Systematic Review of the Landscape

Published:2022 Issue: Volume:10 Page:32190-32212
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Prag Krupa¹^ORCID,Woolway Matthew²^ORCID,Celik Turgay³^ORCID

Affiliation:

1. School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa

2. Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

3. School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09738649.pdf?arnumber=9738649

Reference239 articles.

1. Reinforcement Learning and Dynamic Programming Using Function Approximators

2. Model-free Q-learning designs for linear discrete-time zero-sum games with application to H-infinity control

4. Model-free H∞ control design for unknown linear discrete-time systems via Q-learning with LMI

5. A $Q$-Learning Approach to Derive Optimal Consumption and Investment Strategies

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