{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:40:03Z","timestamp":1755884403454,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T00:00:00Z","timestamp":1695513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871433"],"award-info":[{"award-number":["61871433"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2018A0303130141"],"award-info":[{"award-number":["2018A0303130141"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,9,24]]},"DOI":"10.1145\/3630138.3630420","type":"proceedings-article","created":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T02:04:17Z","timestamp":1705543457000},"page":"1-5","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi-agent reinforcement learning based resource allocation for vehicular networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2908-1586","authenticated-orcid":false,"given":"Jiangnan","family":"Lu","sequence":"first","affiliation":[{"name":"School of Electronics and Information Engineering, South China Normal University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8489-9700","authenticated-orcid":false,"given":"Haixia","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, South China Normal University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4190-1158","authenticated-orcid":false,"given":"Xie","family":"Bo","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, South China Normal University, China"}]}],"member":"320","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Environment-adaptive multiple access for distributed V2X network: A reinforcement learning framework[C]\/\/2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","author":"Kim S","year":"2021","unstructured":"Kim S, Kim B J, Park B B. Environment-adaptive multiple access for distributed V2X network: A reinforcement learning framework[C]\/\/2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). IEEE, 2021: 1-7."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-5130-5"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2974823"},{"key":"e_1_3_2_1_4_1","author":"Khabaz S","year":"2022","unstructured":"Khabaz S, Pujolle G, Braconnot-Velloso P. Resource Allocation Modes in C-V2X: From LTE-V2X to 5G-V2X[J]. IEEE Internet of Things Journal, 2022.","journal-title":"IEEE Internet of Things Journal"},{"key":"e_1_3_2_1_5_1","first-page":"663","article-title":"Access layer specification for Intelligent Transport Systems operating in the 5 GHz frequency band[J]","volume":"302","year":"2019","unstructured":"ITS E, ETSI. G5 Access layer specification for Intelligent Transport Systems operating in the 5 GHz frequency band[J]. EN, 2019, 302: 663.","journal-title":"EN"},{"key":"e_1_3_2_1_6_1","volume-title":"Playing atari with deep reinforcement learning[J]. arXiv preprint arXiv:1312.5602","author":"Mnih V","year":"2013","unstructured":"Mnih V, Kavukcuoglu K, Silver D, Playing atari with deep reinforcement learning[J]. arXiv preprint arXiv:1312.5602, 2013."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2933962"},{"key":"e_1_3_2_1_8_1","first-page":"2399","article-title":"Resource sharing and power allocation for D2D-based safety-critical V2X communications[C]\/\/2015 IEEE International Conference on Communication Workshop (ICCW)","volume":"2015","author":"Sun W","unstructured":"Sun W, Yuan D, Str\u00f6m E G, Resource sharing and power allocation for D2D-based safety-critical V2X communications[C]\/\/2015 IEEE International Conference on Communication Workshop (ICCW). IEEE, 2015: 2399-2405.","journal-title":"IEEE"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOMSTD.2017.1700015"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2018.2888704"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3065996"},{"key":"e_1_3_2_1_12_1","volume-title":"Deep reinforcement learning for distributed dynamic power allocation in wireless networks[J]. arXiv preprint arXiv:1808.00490","author":"Nasir Y S","year":"2018","unstructured":"Nasir Y S, Guo D. Deep reinforcement learning for distributed dynamic power allocation in wireless networks[J]. arXiv preprint arXiv:1808.00490, 2018, 8: 2018."},{"key":"e_1_3_2_1_13_1","volume-title":"Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications[J]","author":"Nguyen T T","year":"2020","unstructured":"Nguyen T T, Nguyen N D, Nahavandi S. Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications[J]. IEEE transactions on cybernetics, 2020, 50(9): 3826-3839."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/su14073879"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2897134"}],"event":{"name":"PCCNT 2023: 2023 International Conference on Power, Communication, Computing and Networking Technologies","acronym":"PCCNT 2023","location":"Wuhan China"},"container-title":["2023 International Conference on Power Communication Computing and Networking Technologies"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3630138.3630420","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3630138.3630420","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:08:58Z","timestamp":1755882538000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3630138.3630420"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,24]]},"references-count":15,"alternative-id":["10.1145\/3630138.3630420","10.1145\/3630138"],"URL":"https:\/\/doi.org\/10.1145\/3630138.3630420","relation":{},"subject":[],"published":{"date-parts":[[2023,9,24]]},"assertion":[{"value":"2024-01-17","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}