Abstract—Predicting the outcomes of social interactions between humans is notoriously difficult. Variations within the experiences, beliefs, and actions of individual humans (and even within a particular given human from one situation to the next) render accurate predictions of the outcome of individual interactions problematic at best. However, it is somewhat easier to make predictions regarding the expected outcome of interactions involving large groups of humans over an extended period. This paper presents a series of studies where simple social interactions between humans of different personality types were modeled over a long term, and where the behavior patterns of individuals within the population were allowed to change. The results of these studies provide predictions for how groups of humans would likely behave in similar situations.
Index Terms—Agent-based simulation, evolutionary modeling, predictive modeling, social interactions.
Barry Webster is with the Florida Institute of Technology, Melbourne, FL 32901 USA (e-mail: bwebster@fit.edu).
Suja Ramakrishnan was formerly with the Florida Institute of Technology, Melbourne, FL 32901. She is now employed by a private company in South Africa (e-mail: suja.ramakrishnan@gmail.com).
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Cite: Barry Webster and Suja Ramakrishnan, "Using Evolutionary Models with Mutations to Predict Long-Term Trends in Simple Social Interactions," International Journal of Modeling and Optimization vol. 5, no. 3, pp. 234-240, 2015.
