TY - JOUR

T1 - Applying Cooperative Games with Coalition Structure for Data Clustering

AU - Bure, V. M.

AU - Staroverova, K. Yu

PY - 2019/8/1

Y1 - 2019/8/1

N2 - This paper considers a cooperative game in which the distance (or similarity) between some objects (players) can be measured numerically. For this game, a characteristic function is defined so that it takes high values for the coalitions consisting of most close (similar) players in comparison with the players from the other coalitions. Such a function does not satisfy superadditivity, and hence it seems reasonable to introduce the model with coalition structure. Therefore, this game can be treated as a clustering procedure for objects (players). Finally, the existence conditions of a stable coalition structure are established, which allow to perform efficient (crisp) clustering.

AB - This paper considers a cooperative game in which the distance (or similarity) between some objects (players) can be measured numerically. For this game, a characteristic function is defined so that it takes high values for the coalitions consisting of most close (similar) players in comparison with the players from the other coalitions. Such a function does not satisfy superadditivity, and hence it seems reasonable to introduce the model with coalition structure. Therefore, this game can be treated as a clustering procedure for objects (players). Finally, the existence conditions of a stable coalition structure are established, which allow to perform efficient (crisp) clustering.

KW - Aumann—Dreze value

KW - clustering

KW - coalition

KW - ESD value

KW - Shapley value

KW - stable coalition structure

UR - http://www.scopus.com/inward/record.url?scp=85070745744&partnerID=8YFLogxK

U2 - 10.1134/S0005117919080125

DO - 10.1134/S0005117919080125

M3 - Article

AN - SCOPUS:85070745744

VL - 80

SP - 1541

EP - 1551

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 8

ER -