{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T15:59:58Z","timestamp":1758815998693,"version":"3.37.3"},"reference-count":18,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1109\/globecom46510.2021.9685236","type":"proceedings-article","created":{"date-parts":[[2022,2,2]],"date-time":"2022-02-02T21:59:04Z","timestamp":1643839144000},"page":"1-6","source":"Crossref","is-referenced-by-count":8,"title":["Mean-Field Game and Reinforcement Learning MEC Resource Provisioning for SFC"],"prefix":"10.1109","author":[{"given":"Amine","family":"Abouaomar","sequence":"first","affiliation":[{"name":"Universit&#x00E9; de Sherbrooke,INTERLAB, Engineering Faculty,Sherbrooke,QC,Canada"}]},{"given":"Soumaya","family":"Cherkaoui","sequence":"additional","affiliation":[{"name":"Universit&#x00E9; de Sherbrooke,INTERLAB, Engineering Faculty,Sherbrooke,QC,Canada"}]},{"given":"Zoubeir","family":"Mlika","sequence":"additional","affiliation":[{"name":"Universit&#x00E9; de Sherbrooke,INTERLAB, Engineering Faculty,Sherbrooke,QC,Canada"}]},{"given":"Abdellatif","family":"Kobbane","sequence":"additional","affiliation":[{"name":"Mohammed V University,ENSIAS,Rabat,Morocco"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM38437.2019.9013429"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.2986851"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3052082"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM38437.2019.9014146"},{"key":"ref14","article-title":"Learning deep mean field games for modeling large population behavior","author":"yang","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref15","first-page":"242","article-title":"Multiagent reinforcement learning: theoretical framework and an algorithm","volume":"98","author":"hu","year":"1998","journal-title":"ICML"},{"key":"ref16","first-page":"49","article-title":"Guided cost learning: Deep inverse optimal control via policy optimization","volume":"48","author":"finn","year":"2016","journal-title":"Proceedings of The 33rd International Conference on Machine Learning ser Proceedings of Machine Learning Research"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CCGrid49817.2020.00-88"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737400"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2019.102429"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000180"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2020.3017001"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3379444"},{"key":"ref8","article-title":"Service function chaining in mec: A mean-field game and reinforcement learning approach","author":"abouaomar","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2020.100298"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034136"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOM.2018.8647858"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2016.2598420"}],"event":{"name":"GLOBECOM 2021 - 2021 IEEE Global Communications Conference","start":{"date-parts":[[2021,12,7]]},"location":"Madrid, Spain","end":{"date-parts":[[2021,12,11]]}},"container-title":["2021 IEEE Global Communications Conference (GLOBECOM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9685019\/9685006\/09685236.pdf?arnumber=9685236","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T20:16:26Z","timestamp":1669666586000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9685236\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1109\/globecom46510.2021.9685236","relation":{},"subject":[],"published":{"date-parts":[[2021,12]]}}}