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• W2582821769 abstract "In a cooperative network, the user equipment (UE) shares information for cooperatively achieving a common goal. However, owing to the concerns of privacy or cost, UEs may be reluctant to share genuine information, which raises the information credibility problem addressed. Diverse techniques have been proposed for enhancing the information credibility in various scenarios. However, there is a paucity of information on modeling the UEs' decision making behavior, namely as to whether they are willing/able to share genuine information, even though this directly affects the information credibility across the network. Hence, we propose a game theoretic framework for the associated information credibility modeling by taking into account the users' information sharing strategies and utilities. This framework is investigated under both a homogeneous model and a heterogeneous model. The spontaneous information credibility equilibria of both models are derived and analyzed, including the closed-form analysis of the homogeneous model based on a sophisticated evolutionary game model and on the reinforcement learning-based analysis of the heterogeneous model. Moreover, a credit mechanism is designed for encouraging the UEs to share genuine information. Experimental results relying on real-world data traces support our utility function formulation, while our simulation results verify the theoretical analysis and show that all the UEs are encouraged by the proposed algorithm to share genuine information with a probability of one, when a credit mechanism is invoked. The proposed modeling techniques may be applied in diverse cooperative networks, including classic wireless networks, vehicular networks, as well as social networks." @default.
• W2582821769 created "2017-02-03" @default.
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• W2582821769 date "2017-02-01" @default.
• W2582821769 modified "2023-10-15" @default.
• W2582821769 title "Information Credibility Modeling in Cooperative Networks: Equilibrium and Mechanism Design" @default.
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• W2582821769 doi "https://doi.org/10.1109/jsac.2017.2659078" @default.
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