检索结果-南通市图书馆

An Incentive Mechanism for Federated Learning:A Continuous zero-determinant strategy Approach

在线全文

学校读者我要写书评

暂无评论

引用

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 88-102页

作者： Changbing Tang Baosen Yang Xiaodong Xie Guanrong Chen Mohammed A.A.Al-qaness Yang Liu IEEE the College of Physics and Electronic Information Engineering Zhejiang Normal UniversityUniversityJinhua 321004China the School of Mathematical Sciences Zhejiang Normal UniversityJinhua 321004China the Department of Electrical Engineering City University of Hong KongHong KongChina Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Jinhua 321004China

As 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 *** 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 ***, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

关键词： Federated learning(FL) game theory incentive mechanism machine learning zero-determinant strategy

zero-determinant strategies in iterated multi-strategy games

在线全文

学校读者我要写书评

暂无评论

引用

纯粹数学与应用数学 2024年第3期40卷 381-393页

作者： GUO Jinli Xi′an Innovation College of Yan’an University Xi′an 710100China Business School University of Shanghai for Science and TechnologyShanghai 200093China

Self-serving,rational agents sometimes cooperate to their mutual *** two-player iterated prisoner′s dilemma game is a model for including the emergence of *** is generally believed that there is no simple ultimatum strategy which a player can control the return of the other *** zero-determinant strategy in the iterated prisoner′s dilemma dramatically expands our understanding of the classic game by uncovering strategies that provide a unilateral advantage to sentient players pitted against unwitting ***,strategies in the prisoner′s dilemma game are only two *** there these results for general multi-strategy games?To address this question,the paper develops a theory for zero-determinant strategies for multi-strategy games,with any number of *** analytical results exhibit a similar yet different scenario to the case of two-strategy *** results are also applied to the Snowdrift game,the Hawk-Dove game and the Chicken game.

关键词： prisoner′s dilemma zero-determinant strategy multi-strategy game symmetric game

A potential game-based outsourcing computation framework for multiple calculators

在线全文

学校读者我要写书评

暂无评论

引用

Digital Communications and Networks 2022年第5期8卷 654-663页

作者： Duo Zhang Youliang Tian Linjie Wang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China School of Mathematics and Statistics Guizhou UniversityGuiyang550025China

Outsourcing computation enables a computationally weak client to outsource the computation of a function f to a more powerful but untrusted *** traditional outsourcing computation model forbids communication between players,but it has little *** on the game theory,this paper establishes an outsourcing computation model which is more in line with the actual ***,we construct a structural mapping relationship between security outsourcing computation and the optimization ***,by designing the individual potential function and the global potential function,the individual goal is consistent with the global goal to ensure the correctness of the calculation ***,in the information exchange environment between calculators,we construct a zero-determinant strategy to ensure that the calculator chooses the strategy according to the predetermined target.

关键词： Outsourcing computation Game theory Potential function zero-determinant strategy Information exchange