Incentive Feedback Stackelberg Strategy in Mean-Field Type Stochastic Difference Games  

作　　者：GAO Wenhui LIN Yaning ZHANG Weihai 

机构地区：[1]School of Mathematics and Statistics,Shandong University of Technology,Zibo 255000,China [2]College of Electrical Engineering and Automation,Shandong University of Science and Technology,Qingdao 266590,China

出　　处：《Journal of Systems Science & Complexity》2024年第4期1425-1445,共21页系统科学与复杂性学报（英文版）

基　　金：supported by the National Natural Science Foundation of China under Grant Nos.61903234 and 61973198;the Natural Science Foundation of Shandong Province under Grant No.ZR2021MA066。

摘　　要：This paper designs an incentive Stackelberg strategy for the discrete-time stochastic systems with mean-field terms.Sufficient conditions for the existence of such a design are suggested.Moreover,the incentive strategy is obtained as a feedback form including the deviation of the state and its mathematical expectation.Also,the stability analysis is involved.It is found that the stability can be guaranteed by the follower.In addition,the specific algorithm is proposed and its effectiveness is checked by two examples.

关 键 词：Discrete-time mean-field stochastic systems incentive strategy Stackelberg game teamoptimal solution 

分 类 号：O225[理学—运筹学与控制论]