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
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