Postdoctoral researcher in the Computer Science Department
University of Maryland College Park
Co-sponsored with Binghamton Bioengineers and Upsilon Pi Epsilon
Evolutionary Game Theoretic and Multi-Agent System Models of the Emergence of Cross-Cultural Differences
Tuesday, October 29, 2013
Science 3 214, 10:00 AM
Our complex human social world has led to the emergence of a vast array of behavior phenomena and cultural differences. Cultural psychologists have classified populations across the world on various cultural scales, including scales of tightness vs. looseness and collectivist vs. individualist. These dichotomies have various behavioral implications. In this talk, I present evolutionary game theoretic and multi-agent system models of social systems that illuminate the emergence of various cross-cultural behavioral differences relating to these scales. Some of the phenomena I will explore include differences in punishment norms, third-party punishment, and group-based vs. individualistic thinking. I show individual interactions and adaptation processes under different contextual factors can lead to the emergence of population-level differences in these phenomena. By providing explicit, bottom-up, and explanatory models of the emergence of these differences, the presented models help establish support for causal relationships that are often difficult or impossible to test empirically. These models also help promote cross-cultural understanding by showing how cultural differences, which may appear puzzling, can be adaptive to societies’ ecological and historical context.
Patrick Roos is a postdoctoral researcher in the Computer Science Department at the University of Maryland, working jointly with the Department of Psychology. His interdisciplinary research has spanned the computational, social, and life sciences as well as the humanities. While attaining his B.S. in Discovery Informatics from the College of Charleston, his research employed data mining and evolutionary computation approaches to music information retrieval and computational aesthetics. He received his M.S. and Ph.D. in Computer Science at the University of Maryland, focusing on evolutionary game theoretic modeling of the evolution of human risk preferences and decision-making. His current research is focused on extending the development of evolutionary game theoretic and multi-agent system models to study a variety of behavioral phenomena in human social systems. This work seeks to enhance and progress the understanding of our complex human social world by illuminating how evolutionary behavioral outcomes and dynamics relate to various contextual factors and cultural adaptation processes. His work has led to numerous peer-reviewed publications in interdisciplinary journals and conferences, a book chapter, and multiple presentations at international conferences.