Normalized mutual entropy in biology: Quantifying division of Labor

被引:49
作者
Gorelick, R [1 ]
Bertram, SM
Killeen, PR
Fewell, JH
机构
[1] Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA
[2] Arizona State Univ, Dept Psychol, Tempe, AZ 85287 USA
关键词
information theory; entropy; task specialization; division of labor;
D O I
10.1086/424968
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Division of labor is one of the primary adaptations of sociality and the focus of much theoretical work on self-organization. This work has been hampered by the lack of a quantitative measure of division of labor that can be applied across systems. We divide Shannon's mutual entropy by marginal entropy to quantify division of labor, rendering it robust over changes in number of individuals or tasks. Reinterpreting individuals and tasks makes this methodology applicable to a wide range of other contexts, such as breeding systems and predator-prey interactions.
引用
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页码:677 / 682
页数:6
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