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Potential analysis of a Quantum RL controller in the context of autonomous driving

Hickmann, Manuel Lautaro and Raulf, Arne Peter and Köster, Frank and Schwenker, Friedhelm and Rieser, Hans-Martin (2023) Potential analysis of a Quantum RL controller in the context of autonomous driving. In: 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2023, pp. 263-268. Ciaco - i6doc.com. ESANN ( European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning) 2023, 4-6 October 2023, Bruges, Belgium. doi: 10.14428/esann/2023.ES2023-22. ISBN 978-2-87587-088-9.

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Official URL: https://www.esann.org/sites/default/files/proceedings/2023/ES2023-22.pdf

Abstract

The potential of quantum enhanced Q-learning with a focus on its applicability to a lane change manoeuvre is investigated. In this context we solve multiple simple reinforcement learning environments using variational quantum circuits. The achieved results were similar to or even better than those of a simple constrained classical agent. We could observe promising behaviour on the more complex lane change manoeuvre task, which has an environment with an observation vector size twice larger than commonly used ones. For the Frozen Lake environment we found indications of possible quantum advantages in convergence rate.

Item URL in elib:https://elib.dlr.de/198199/
Document Type:Conference or Workshop Item (Poster)
Title:Potential analysis of a Quantum RL controller in the context of autonomous driving
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Hickmann, Manuel LautaroUNSPECIFIEDhttps://orcid.org/0000-0002-9501-4004144909437
Raulf, Arne PeterUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Köster, FrankUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schwenker, FriedhelmUniversität UlmUNSPECIFIEDUNSPECIFIED
Rieser, Hans-MartinUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2023
Journal or Publication Title:31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2023
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI:10.14428/esann/2023.ES2023-22
Page Range:pp. 263-268
Editors:
EditorsEmailEditor's ORCID iDORCID Put Code
Verleysen, MichelUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Publisher:Ciaco - i6doc.com
Series Name:ESANN 2023 proceedings
ISBN:978-2-87587-088-9
Status:Published
Keywords:Quantum Machine Learning, Quantum Neural Networks, Reinforcement Learning, Quantum Reinforcement Learning, Autonomous Driving, Trajectory Planning, Variational Quantum Circuits
Event Title:ESANN ( European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning) 2023
Event Location:Bruges, Belgium
Event Type:international Conference
Event Dates:4-6 October 2023
Organizer:UCLouvain - Machine Learning Group
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:other
DLR - Research area:Transport
DLR - Program:V - no assignment
DLR - Research theme (Project):V - no assignment, R - Reinforcement learning with quantum algorithms, D - short study [KIZ]
Location: Ulm
Institutes and Institutions:Institute for AI Safety and Security
Deposited By: Hickmann, Manuel Lautaro
Deposited On:20 Oct 2023 12:39
Last Modified:20 Oct 2023 12:39

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