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A machine learning-based framework for user recruitment in continuous mobile crowdsensing., , , , и . Ad Hoc Networks, (июня 2023)Multiagent Deep Reinforcement Learning With Demonstration Cloning for Target Localization., , , , и . IEEE Internet Things J., 10 (15): 13556-13570 (августа 2023)A Context-Aware Blockchain-Based Crowdsourcing Framework: Open Challenges and Opportunities., , , и . IEEE Access, (2022)A Survey on Explainable Artificial Intelligence for Cybersecurity., , , , , , , и . IEEE Trans. Netw. Serv. Manag., 20 (4): 5115-5140 (декабря 2023)Towards a best-effort framework for developing smart mobile applications., , и . IWCMC, стр. 752-757. IEEE, (2012)Two-sided preferences task matching mechanisms for blockchain-based crowdsourcing., , , , и . J. Netw. Comput. Appl., (2021)GRS: A Group-Based Recruitment System for Mobile Crowd Sensing., , , , и . J. Netw. Comput. Appl., (2016)A greedy-proof incentive-compatible mechanism for group recruitment in mobile crowd sensing., , , , и . Future Gener. Comput. Syst., (2019)A Cluster-based Quality-of-Service Optimized Link State Routing protocol for Mesh Networks., , , , , , и . IWCMC, стр. 336-341. IEEE, (2022)Bridging the gap: empowering use cases with task models., , и . EICS, стр. 291-296. ACM, (2010)