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Evolutionary Perspective on Collective Decision Making

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This project was supported by the NSF Human and Social Dynamics Program (Award #: NSF SES-0826711).
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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About the Project

Collective decision making plays an increasingly important role everywhere in today's human society. Existing literature addresses issues in collective decision making with linear statistical analysis or relatively simple dynamical modeling. Either approach is still limited in capturing the complexity of real human decision making dynamics that typically involve high-dimensional nonlinear problem space, nontrivial societal structure, within-individual cognitive and behavioral patterns, and/or between-individual diversity.

In this NSF-funded project which ran from 2008 through 2012, researchers developed and proposed novel conceptual/computational multi-level models of the dynamics of complex collective decision making by uniquely shifting the viewpoint from the dynamics of participants to the dynamics of ideas being discussed. In the proposed framework, collective decision making is redefined as evolution of ecologies of ideas over a social network habitat, where populations of potential solutions evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of solutions, each conducted by participating humans. The effects of various model assumptions on collective decision making were studied through computer simulations, and their results were validated through experiments of team decision making on complex collaborative tasks with human subjects.

This project presented a novel perspective on human and social dynamics by introducing evolutionary principles and methodologies into the modeling of their complex behaviors, making a theoretical advancement from a traditional, individually-focused psychological or social science paradigm to a more dynamic, multilevel, evolutionary paradigm for collective social processes. The project outcomes include a number of practical implications, e.g., the effects of coherence of shared information and organizational structure within teams upon their exploratory and adaptive performances, which will be widely applicable to current issues that many human organizations are facing today. The outcomes of this project has been integrated into undergraduate and graduate education at Binghamton University.


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Contact Us

Please address any inquiries about this project to:

Hiroki Sayama, D.Sc.
Director, Collective Dynamics of Complex Systems Research Group
Associate Professor, Departments of Bioengineering & Systems Science and Industrial Engineering
Binghamton University, State University of New York
P.O. Box 6000, Binghamton, NY 13902-6000
Email: sayama@binghamton.edu
Tel: (607) 777-4439
Fax: (607) 777-5780


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