Defeating Terrorist Networks with Game Theory

被引:20
作者
Michalak, Tomasz P. [1 ]
Rahwan, Talal [2 ]
Skibski, Oskar [3 ]
Wooldridge, Michael [1 ]
机构
[1] Univ Oxford, Dept Comp Sci, Oxford OX1 2JD, England
[2] Masdar Inst Sci & Technol, Comp & Informat Sci Dept, Abu Dhabi, U Arab Emirates
[3] Kyushu Univ, Dept Comp Sci, Fukuoka 812, Japan
基金
欧洲研究理事会;
关键词
CENTRALITY;
D O I
10.1109/MIS.2015.11
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One key problem is that of identifying the key members of the organization using information about the terrorist network's topology: this capability would enable security agencies to focus severely limited resources on just those key members. many standard measures of centrality from the field of social network analysis can be used. Centrality measures aim to give a numerical characterization of a node's significance in a network. In contrast, according to closeness centrality, a node's importance is based on the average distance between that node and other nodes in the network. Although the standard measures indeed deliver nontrivial insights, they cannot capture certain important aspects of centrality in a terrorist organization. Unfortunately, due to their inherent combinatorial nature, computing solution concepts for coalitional games is often computationally challenging.
引用
收藏
页码:53 / 61
页数:9
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