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Computational and Mathematical Organization Theory

, Volume 20, Issue 3, pp 302–337 | Cite as

Cognitive modeling of socially transmitted affordances: a computational model of behavioral adoption tested against archival data from the Stanford Prison Experiment

  • Benjamin D. Nye
SI BRIMS 2012

Abstract

Social learning and adoption of new affordances govern the rise of new a variety of behaviors, from actions as mundane as dance steps to those as dangerous as new ways to make improvised explosive device (IED) detonators. Traditional diffusion models and social network structures fail to adequately explain who would be likely to imitate new behavior and why some agents adopt the behavior while others do not. To address this gap, a cognitive model was designed that represents well-known socio-cognitive factors of attention, social influence, and motivation that influence learning and adoption of new behavior. This model was implemented in the Performance Moderator Function Server (PMFServ) agent-based cognitive architecture, enabling the creation of simulations where affordances spread memetically through cognitive mechanisms. This approach models facets of behavioral adoption that have not been explored by existing architectures: unintentional learning, multi-layered social and environmental attention cues, and contextual adoption. To examine the effectiveness of this model, its performance was tested against data from the Stanford Prison Experiment collected from the Archives of the History of American Psychology.

Keywords

Social learning Affordances Cognitive modeling Cognitive agents Social influence Memes 

Notes

Acknowledgements

Thank you to the Air Force Office of Scientific Research, whose basic research support made this work possible. Also, my sincere thanks to Professor Zimbardo, who was exceptionally responsive and helpful in arranging my access to the archival Stanford Prison Experiment data. Finally, I would like to give a special thanks to the Archives of the History of American Psychology which graciously allowed me to collect data on-site for many days.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Ackoff Center for Advancement of Systems ApproachesUniversity of PennsylvaniaPhiladelphiaUSA

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