基于演化博弈模型的群智感知网络激励机制  

Incentive mechanism of mobile group intelligence perception network based on evolutionary game model

作　　者：赵宇红[1] 包凤莲 ZHAO Yuhong;BAO Fenglian(Information Engineering School, Inner Mongolia university of science and technology, Baotou 014010, China;Third Staff and Workers Hospital, Baotou Iron and Steel (Group) Co., Baotou 014010, China)

机构地区：[1]内蒙古科技大学信息工程学院,内蒙古包头014010 [2]包钢集团第三职工医院,内蒙古包头014010

出　　处：《内蒙古科技大学学报》2020年第4期363-368,共6页Journal of Inner Mongolia University of Science and Technology

基　　金：国家自然科学基金资助项目(61562065).

摘　　要：提出一种基于演化博弈模型的激励机制(IMEG),鼓励参与者参与感知活动及分享参与者间的数据信息.机制以用户收益为核心,首先,利用演化博弈中“适者生存”思想,构建每个参与者在博弈过程中更新、学习行为策略,以获取更多的收益;然后,设计了参与者的合作度调节收益;调整下一轮博弈中参与者的博弈次数;感知服务平台调整收益.更新策略、筛选学习对象,完成整个演化博弈过程,达到促进参与者协作、共享数据的目标.实验结果表明:与TRAC和IMC-SS激励机制相比,所提的IMEG能提高用户平均效用、任务覆盖率和任务完成率.Aiming at solving the problem of information sharing between users,a mobile intelligence perception model(IMEG)based on evolutionary games was proposed.Game participants were encouraged to participate in perception activities and share data and information among them.The basic idea of“survival of the fittest”was used in evolutionary games for each participant to update and learn behavioral strategies during the game to obtain more benefits.And the number of participants’games in the next round of evolution was adjusted.The participant income was adjusted by perception service platform to control the entire evolutionary game process,update the strategy,filter the learning objects and complete the entire game process.The evolutionary game process promoted cooperation and data sharing among participants.Experimental results show that compared with TRAC and IMC-SS incentive mechanisms,the IMEG has higher average utility in task coverage and task completion rate.

关 键 词：激励机制 移动群智感知 演化博弈 自私节点 

分 类 号：TN929.5[电子电信—通信与信息系统]