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Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning

Junxiu Liu Orcid Logo, Sheng Qin Orcid Logo, Yuling Luo Orcid Logo, Yanhu Wang, Scott Yang Orcid Logo

IEEE Transactions on Vehicular Technology, Volume: 71, Issue: 6, Pages: 5960 - 5970

Swansea University Author: Scott Yang Orcid Logo

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DOI (Published version): 10.1109/tvt.2022.3160871

Published in: IEEE Transactions on Vehicular Technology
ISSN: 0018-9545 1939-9359
Published: Institute of Electrical and Electronics Engineers (IEEE) 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa60406
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first_indexed 2022-07-07T16:46:45Z
last_indexed 2023-01-13T19:20:30Z
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spelling 2022-07-07T17:46:54.1407489 v2 60406 2022-07-07 Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning 81dc663ca0e68c60908d35b1d2ec3a9b 0000-0002-6618-7483 Scott Yang Scott Yang true false 2022-07-07 SCS Journal Article IEEE Transactions on Vehicular Technology 71 6 5960 5970 Institute of Electrical and Electronics Engineers (IEEE) 0018-9545 1939-9359 1 6 2022 2022-06-01 10.1109/tvt.2022.3160871 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University This work was supported in part by the National Natural Science Foundation of China under Grant 61976063, and in part by the Guangxi Natural Science Foundation under Grant 2021JJG170015. 2022-07-07T17:46:54.1407489 2022-07-07T17:42:53.9203143 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Junxiu Liu 0000-0002-9790-1571 1 Sheng Qin 0000-0001-7348-901x 2 Yuling Luo 0000-0002-0117-4614 3 Yanhu Wang 4 Scott Yang 0000-0002-6618-7483 5
title Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
spellingShingle Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
Scott Yang
title_short Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
title_full Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
title_fullStr Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
title_full_unstemmed Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
title_sort Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning
author_id_str_mv 81dc663ca0e68c60908d35b1d2ec3a9b
author_id_fullname_str_mv 81dc663ca0e68c60908d35b1d2ec3a9b_***_Scott Yang
author Scott Yang
author2 Junxiu Liu
Sheng Qin
Yuling Luo
Yanhu Wang
Scott Yang
format Journal article
container_title IEEE Transactions on Vehicular Technology
container_volume 71
container_issue 6
container_start_page 5960
publishDate 2022
institution Swansea University
issn 0018-9545
1939-9359
doi_str_mv 10.1109/tvt.2022.3160871
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
active_str 0
published_date 2022-06-01T04:18:29Z
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score 11.012678

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