Abstract
Suboptimal restraint use is a prevalent problem worldwide. In developed countries injuries and deaths related to vehicle accidents persist despite increases in restraint use. In this study we investigate the emergence of patterns of restraint use in groups of agents and the population at large. Using age as an influential factor we simulate random encounters between group members where dominant individuals repeatedly alter the knowledge of less influential individuals. Belief spaces implemented as part of a cultural algorithm are used to preserve prevalent patterns of restraint use both at the group and population levels. The objective is to demonstrate restraint selection and use patterns emerging within a population and to determine whether a focus on influential members might have a positive effect towards optimal restraint use. We demonstrate that prominent patterns of behavior similar to the influential members of the groups do emerge both in the presence of social and cultural influence.
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Mokom, F., Kobti, Z. (2013). Suboptimal Restraint Use as an Emergent Norm via Social Influence. In: Omatu, S., Neves, J., Rodriguez, J., Paz Santana, J., Gonzalez, S. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-00551-5_65
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DOI: https://doi.org/10.1007/978-3-319-00551-5_65
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00550-8
Online ISBN: 978-3-319-00551-5
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