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On the Use of Quantum Reinforcement Learning in Energy-Efficiency Scenarios

On the Use of Quantum Reinforcement Learning in Energy-Efficiency Scenarios

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_401f24a3c24c4959b1426f1743b8a0a7

On the Use of Quantum Reinforcement Learning in Energy-Efficiency Scenarios

About this item

Full title

On the Use of Quantum Reinforcement Learning in Energy-Efficiency Scenarios

Publisher

Basel: MDPI AG

Journal title

Energies (Basel), 2022-08, Vol.15 (16), p.6034

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

In the last few years, deep reinforcement learning has been proposed as a method to perform online learning in energy-efficiency scenarios such as HVAC control, electric car energy management, or building energy management, just to mention a few. On the other hand, quantum machine learning was born during the last decade to extend classic machine l...

Alternative Titles

Full title

On the Use of Quantum Reinforcement Learning in Energy-Efficiency Scenarios

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_401f24a3c24c4959b1426f1743b8a0a7

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_401f24a3c24c4959b1426f1743b8a0a7

Other Identifiers

ISSN

1996-1073

E-ISSN

1996-1073

DOI

10.3390/en15166034

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