@inbook{ab9b8ada8ab44049968d1622500b9103,
title = "Incentive Mechanism Design for Mobile Crowdsourcing Without Verification",
abstract = "This chapter studies the design of incentive mechanisms for mobile crowdsourcing systems in which verifying the underlying ground truth is not possible. Namely, we consider a crowdsourcing platform that seeks to incentivize a group of workers to put in effort and truthfully report solutions to a given task. Challenges in this setting include that the workers may have heterogeneous capabilities and may have an incentive to collude in order to deceive the platform. The platform itself may have incomplete information regarding the workers{\textquoteright} capabilities, which it could attempt to learn over time. Furthermore, there may be asymmetries in the information available to the platform and to the workers. We will survey approaches to dealing with such problems using game-theoretical and online learning-based approaches.",
keywords = "Game-theoretical, Incentive mechanism, Mobile crowdsensing, Online learning",
author = "Chao Huang and Haoran Yu and Jianwei Huang and Randall Berry",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2023",
doi = "10.1007/978-3-031-32397-3_5",
language = "English",
series = "Wireless Networks (United Kingdom)",
publisher = "Springer Nature",
pages = "117--140",
booktitle = "Wireless Networks (United Kingdom)",
address = "Switzerland",
}