DocumentCode :
2471306
Title :
An individual-based evolutionary dynamics model for networked social behaviors
Author :
Hussein, Islam I.
Author_Institution :
Mech. Eng., Worcester Polytech. Inst., Worcester, MA, USA
fYear :
2009
fDate :
10-12 June 2009
Firstpage :
5789
Lastpage :
5796
Abstract :
In this paper, an evolutionary dynamics model over a graph of connected individuals choosing between multiple behaviors is developed. This model emphasizes the individuality of the nodes, which arrive at individual behavioral choices primarily based on subjective individual preferences as well as individual mutation characteristics. We use the replicator-mutator dynamical equations to model the process of building individual behavioral inclinations. A dynamic graph, whose vertices are the individual members of society, is then constructed and the weighted adjacency matrix and individual fitness parameters are used to effect a social interaction model that is itself modeled based on the replicator-mutator dynamical equations. A notion of social diversity is defined for this individual-based social choice model. The individual-based social evolutionary model presented here relates to and generalizes three previous models appearing in the literature: the replicator-mutator social choice model, consensus algorithms, and an evolutionary dynamic model on graphs. The basic properties and conditions for the emergence of an absolutely dominant behavior over the social network are derived, and how the proposed model generalizes and relates to other work is also discussed.
Keywords :
behavioural sciences; evolutionary computation; social sciences; dynamic graph; individual behavioral choices; individual mutation characteristics; individual-based evolutionary dynamics model; networked social behaviors; replicator-mutator dynamical equations; social diversity; subjective individual preferences; weighted adjacency matrix; Biological system modeling; Buildings; Cost accounting; Cultural differences; Equations; Evolution (biology); Genetic mutations; Mechanical engineering; Organisms; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
ISSN :
0743-1619
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2009.5160400
Filename :
5160400
Link To Document :
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