Improving polynomial estimation of the Shapley value by stratified random sampling with optimum allocation

被引:50
|
作者
Castro, Javier [1 ]
Gomez, Daniel [1 ]
Molina, Elisenda [2 ]
Tejada, Juan [3 ]
机构
[1] Univ Complutense Madrid, Fac Estudios Estadist, Dept Estadist & IO 3, E-28040 Madrid, Spain
[2] Univ Carlos III Madrid, Dept Estadist, Calle Madrid 126, Madrid 28903, Spain
[3] Univ Complutense Madrid, Fac Ciencias Matemat, IMI, Dept Estadist & Invest Operat, Plaza Ciencias 3, E-28040 Madrid, Spain
关键词
Computer science; Game theory; Operations research; Shapley value; Stratified sampling algorithm; MICROARRAY GAMES; COMPLEXITY; NETWORKS; POWER;
D O I
10.1016/j.cor.2017.01.019
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we propose a refinement of the polynomial method based on sampling theory proposed by Castro et al. (2009) to estimate the Shapley value for cooperative games. In addition to analyzing the variance of the previously proposed estimation method, we employ stratified random sampling with optimum allocation in order to reduce the variance. We examine some desirable statistical features of the stratified approach and provide some computational results by analyzing the gains due to stratification, which are around 30% on average and more than 80% in the best case. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:180 / 188
页数:9
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