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An Incentive Mechanism for Federated Learning: A Continuous Zero-Determinant Strategy Approach
Changbing Tang; Baosen Yang; Xiaodong Xie; Guanrong Chen; Mohammed A. A. Al-qaness; Yang Liu
Source PublicationIEEE/CAA Journal of Automatica Sinica
ISSN2329-9266
2024
Volume11Issue:1Pages:88-102
AbstractAs a representative emerging machine learning technique, federated learning (FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution. These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant (CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL. Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.
KeywordFederated learning (FL) game theory incentive mechanism machine learning zero-determinant strategy
DOI10.1109/JAS.2023.123828
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Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/54495
Collection学术期刊_IEEE/CAA Journal of Automatica Sinica
Recommended Citation
GB/T 7714
Changbing Tang,Baosen Yang,Xiaodong Xie,et al. An Incentive Mechanism for Federated Learning: A Continuous Zero-Determinant Strategy Approach[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(1):88-102.
APA Changbing Tang,Baosen Yang,Xiaodong Xie,Guanrong Chen,Mohammed A. A. Al-qaness,&Yang Liu.(2024).An Incentive Mechanism for Federated Learning: A Continuous Zero-Determinant Strategy Approach.IEEE/CAA Journal of Automatica Sinica,11(1),88-102.
MLA Changbing Tang,et al."An Incentive Mechanism for Federated Learning: A Continuous Zero-Determinant Strategy Approach".IEEE/CAA Journal of Automatica Sinica 11.1(2024):88-102.
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