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, 2023-10-04 - 2023-10-06, 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:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Hickmann, Manuel Lautaro	UNSPECIFIED	https://orcid.org/0000-0002-9501-4004	144909437
Raulf, Arne Peter	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Köster, Frank	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Schwenker, Friedhelm	Universität Ulm	UNSPECIFIED	UNSPECIFIED
Rieser, Hans-Martin	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

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:

In SCOPUS:

In ISI Web of Science:

DOI:

10.14428/esann/2023.ES2023-22

Page Range:

pp. 263-268

Editors:

Editors	Email	Editor's ORCID iD	ORCID Put Code
Verleysen, Michel	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

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 Start Date:

4 October 2023

Event End Date:

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:

24 Apr 2024 20:58

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