loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Author: Przemysław Klȩsk

Affiliation: Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. ˙Zołnierska 49, 71-210 Szczecin, Poland

Keyword(s): Car Parking, Double Q-Learning, Neural Approximations, Parameterized Reward Functions, State Representations.

Abstract: We consider a simple parking problem where the goal for the learning agent is to park the car from a range of initial random positions to a target place with front and back end-points distinguished, without obstacles in the scene but with an imposed time regime, e.g. 25s. It is a sequential decision problem with a continuous state space and a high frequency of decisions to be taken. We employ the double Q-learning computational approach, using the bang–bang control and neural approximations for the Q functions. Our main focus is laid on the design of rewards and state representations for this problem. We propose a family of parameterized reward functions that include, in particular, a penalty for the so-called “gutter distance”. We also study several variants of vector state representations that (apart from observing velocity and direction) relate some key points on the car with key points in the park place. We show that a suitable combination of the state representation and rewards can effectively guide the agent towards better trajectories. Thereby, the learning procedure can be carried out within a reasonably small number of episodes, resulting in high success rate at the testing stage. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.128.181.81

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Klȩsk, P. (2025). Double Q-Learning for a Simple Parking Problem: Propositions of Reward Functions and State Representations. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-737-5; ISSN 2184-433X, SciTePress, pages 156-171. DOI: 10.5220/0013302100003890

@conference{icaart25,
author={Przemysław Klȩsk},
title={Double Q-Learning for a Simple Parking Problem: Propositions of Reward Functions and State Representations},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2025},
pages={156-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013302100003890},
isbn={978-989-758-737-5},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Double Q-Learning for a Simple Parking Problem: Propositions of Reward Functions and State Representations
SN - 978-989-758-737-5
IS - 2184-433X
AU - Klȩsk, P.
PY - 2025
SP - 156
EP - 171
DO - 10.5220/0013302100003890
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic