{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T10:58:12Z","timestamp":1776941892911,"version":"3.51.4"},"reference-count":35,"publisher":"Tech Science Press","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.059880","type":"journal-article","created":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T01:34:56Z","timestamp":1736127296000},"page":"4431-4449","source":"Crossref","is-referenced-by-count":1,"title":["MARCS: A Mobile Crowdsensing Framework Based on Data Shapley Value Enabled Multi-Agent Deep Reinforcement Learning"],"prefix":"10.32604","volume":"82","author":[{"given":"Yiqin","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufeng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhua","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qun","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1145\/3481621","article-title":"Crowdsensing 2. 0","volume":"64","author":"Yu","year":"2021","journal-title":"Commun ACM"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1145\/2794400","article-title":"Mobile crowd sensing and computing: the review of an emerging human-powered sensing paradigm","volume":"48","author":"Guo","year":"2015","journal-title":"ACM Comput Surv"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/MCOM.2014.6871666","article-title":"Opportunities in mobile crowd sensing","volume":"52","author":"Ma","year":"2014","journal-title":"IEEE Commun Mag"},{"key":"ref4","first-page":"517","article-title":"A crowdsensing market based on game theory: Participant incentive, task assignment and pricing guidance","volume":"28","author":"Wu","year":"2022","journal-title":"Int J Commun Netw Distrib Syst"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"14971","DOI":"10.1109\/JIOT.2021.3072953","article-title":"Biobjective robust incentive mechanism design for mobile crowdsensing","volume":"8","author":"Xu","year":"2021","journal-title":"IEEE Internet Things J"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1109\/TMC.2022.3232513","article-title":"An ordered submodularity-based budget-feasible mechanism for opportunistic mobile crowdsensing task allocation and pricing","volume":"23","author":"Zhang","year":"2024","journal-title":"IEEE Trans Mobile Comput"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"5064","DOI":"10.1109\/TNNLS.2022.3207346","article-title":"Deep reinforcement learning: a survey","volume":"35","author":"Wang","year":"2024","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/TIFS.2017.2737968","article-title":"A secure mobile crowdsensing game with deep reinforcement learning","volume":"13","author":"Xiao","year":"2018","journal-title":"IEEE Trans Inf Forens Secur"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1007\/s10462-021-09996-w","article-title":"Multi-agent deep reinforcement learning: A survey","volume":"55","author":"Gronauer","year":"2022","journal-title":"Artif Intell Rev"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"3826","DOI":"10.1109\/TCYB.2020.2977374","article-title":"Deep reinforcement learning for multi-agent systems: a review of challenges, solutions and applications","volume":"50","author":"Nguyen","year":"2020","journal-title":"IEEE Trans Cybern"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"3190","DOI":"10.1109\/TPDS.2013.2297112","article-title":"Free market of crowdsourcing: incentive mechanism design for mobile sensing","volume":"25","author":"Zhang","year":"2014","journal-title":"IEEE Trans Parall Distrib Syst"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TMC.2017.2743718","article-title":"Scalable mobile crowdsensing via peer-to-peer data sharing","volume":"17","author":"Jiang","year":"2018","journal-title":"IEEE Trans Mobile Comput"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1109\/TMC.2019.2892953","article-title":"A distributed game methodology for crowdsensing in uncertain wireless scenario","volume":"19","author":"Cao","year":"2020","journal-title":"IEEE Trans Mobile Comput"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.comnet.2017.12.013","article-title":"Incentive mechanism in platform-centric mobile crowdsensing: a one-to-many bargaining approach","volume":"132","author":"Zhan","year":"2018","journal-title":"Comput Netw"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1109\/JIOT.2017.2779176","article-title":"Incentive mechanism design in mobile opportunistic data collection with time sensitivity","volume":"5","author":"Zhan","year":"2018","journal-title":"IEEE Internet Things J"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1109\/THMS.2016.2599489","article-title":"ActiveCrowd: a framework for optimized multitask allocation in mobile crowdsensing systems","volume":"47","author":"Guo","year":"2017","journal-title":"IEEE Trans Human-Mach Syst"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"1494","DOI":"10.1109\/TMC.2019.2962457","article-title":"Multi-task allocation under time constraints in mobile crowdsensing","volume":"20","author":"Li","year":"2021","journal-title":"IEEE Trans Mobile Comput"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1109\/TVT.2016.2647624","article-title":"Mobile crowdsensing games in vehicular networks","volume":"67","author":"Xiao","year":"2018","journal-title":"IEEE Trans Veh Technol"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"10923","DOI":"10.1109\/TVT.2022.3183607","article-title":"PSARE: a RL-based online participant selection scheme incorporating area coverage ratio and degree in mobile crowdsensing","volume":"71","author":"Xu","year":"2022","journal-title":"IEEE Trans Veh Technol"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2020.03.109","article-title":"An incentive mechanism design for mobile crowdsensing with demand uncertainties","volume":"528","author":"Zhan","year":"2020","journal-title":"Inf Sci"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"2316","DOI":"10.1109\/TMC.2019.2927314","article-title":"Free market of multi-leader multi-follower mobile crowdsensing: an incentive mechanism design by deep reinforcement learning","volume":"19","author":"Zhan","year":"2020","journal-title":"IEEE Trans Mobile Comput"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1109\/TNSE.2022.3226422","article-title":"Intelligent task allocation for mobile crowdsensing with graph attention network and deep reinforcement learning","volume":"10","author":"Xu","year":"2023","journal-title":"IEEE Trans Netw Sci Eng"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1109\/TETCI.2020.3042244","article-title":"IntelligentCrowd: mobile crowdsensing via multi-agent reinforcement learning","volume":"5","author":"Chen","year":"2021","journal-title":"IEEE Trans Emerg Topics Comput Intell"},{"key":"ref24","series-title":"Proceeding of the IEEE Global Communications Conference (GLOBECOM)","first-page":"4436","article-title":"Federated deep reinforcement learning for task participation in mobile crowdsensing","author":"Dongare","year":"2023"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"16564","DOI":"10.1109\/JIOT.2023.3268846","article-title":"Decentralized task assignment for mobile crowd-sensing with multi-agent deep reinforcement learning","volume":"10","author":"Xu","year":"2023","journal-title":"IEEE Internet Things J"},{"key":"ref26","first-page":"7285","article-title":"Shapley Q-value: a local reward approach to solve global reward games","volume":"34","author":"Wang","year":"2020","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1007\/s11403-020-00297-z","article-title":"Decision-facilitating information in hidden-action setups: an agent-based approach","volume":"16","author":"Leitner","year":"2021","journal-title":"J Econ Interact Coord"},{"key":"ref28","series-title":"Proceeding of the Thirty-First International Joint Conference on Artificial Intelligence","first-page":"5572","article-title":"The shapley value in machine learning","author":"Rozemberczki","year":"2023"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/MCI.2021.3129959","article-title":"Collective explainable AI: explaining cooperative strategies and agent contribution in multiagent reinforcement learning with shapley values","volume":"17","author":"Heuillet","year":"2022","journal-title":"IEEE Comput Intell Mag"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1038\/s42256-023-00657-x","article-title":"Algorithms to estimate Shapley value feature attributions","volume":"5","author":"Chen","year":"2023","journal-title":"Nature Mach Intell"},{"key":"ref31","first-page":"5941","article-title":"SHAQ: incorporating Shapley value theory into multi-agent Q-learning","volume":"35","author":"Wang","year":"2022","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref32","series-title":"Proceeding of Advances in Neural Information Processing Systems","first-page":"6379","article-title":"Multiagent actor-critic for mixed cooperative-competitive environments","author":"Lowe","year":"2017"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"3505","DOI":"10.1021\/ie900323c","article-title":"Model predictive control tuning methods: a review","volume":"49","author":"Garriga","year":"2010","journal-title":"Indus Eng Chem Res"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"103327","DOI":"10.1016\/j.jprocont.2024.103327","article-title":"Data science and model predictive control: a survey of recent advances on data-driven MPC algorithms","volume":"144","author":"Morato","year":"2024","journal-title":"J Process Control"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"10600","DOI":"10.1109\/JIOT.2023.3326820","article-title":"MADDPG-based joint service placement and task offloading in MEC empowered air-ground integrated networks","volume":"11","author":"Du","year":"2024","journal-title":"IEEE Internet Things J"}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-82-3\/TSP_CMC_59880\/TSP_CMC_59880.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:29:18Z","timestamp":1763101758000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v82n3\/59913"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":35,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.059880","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}