Community

David Earnest Member since: Saturday, March 13, 2010 Full Member Reviewer

Ph.D. in political science (2004), M.A. in security policy studies (1994)

Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.

I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.

While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.

Carlos M Fernández-Márquez Member since: Friday, May 17, 2013

Ph.D., Economics, Universidad Autonoma de Madrid, Degree in Economics, Degree in Computer Science

ABM applied to socio-economic systems: opinion evolution, industry dynamics, spatial models of voting, diffusion of innovations, macroeconomic with microfoundations, etc.

Rodrigo Garcia-Herrera Member since: Tuesday, February 05, 2019

B.Sc. Cibernetics, M. Sc. Complexity

Match-making platforms for sociocultural change.

Victoria Ramenzoni Member since: Saturday, July 23, 2016

Ph.D.

Human behavioral ecology, marine ecology, cognitive sciences, decision making under uncertainty

Wade Brorsen Member since: Tuesday, June 03, 2014

Ph.D. Texas A&M University, B.S., M.S. Oklahoma State University, M.S. (statistics) University of Wisconsin

Quantitative research in economics.

Karandeep Singh Member since: Tuesday, December 19, 2017

Ph. D., Computer Software, M. E., Computer Science and Enginnering, B. Tech., Computer Engineering

Currently working on Agent Based Demography.

Christopher Thron Member since: Saturday, November 07, 2015

Ph.D. in physics, University of Kentucky, Ph.D. in mathematics, University of Wisconsin

Mathematical modeling and simulation in social sciences, biology, physics, and signal processing.

Sae Schatz Member since: Tuesday, November 04, 2014

Modeling and Simulation, Ph.D., Modeling and Simulation, M.S., Computer Information Technology, B.S.

Sae Schatz, Ph.D., is an applied human–systems researcher, professional facilitator, and cognitive scientist. Her work focuses on human–systems integration (HSI), with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation (M&S). Frequently, her work seeks to enhance individual’s higher-order cognitive skills (i.e., the mental, emotional, and relational skills associated with “cognitive readiness”).

Colin Wren Member since: Tuesday, April 16, 2013 Full Member

B.A., Anthropology, McGill University, M.Sc., GIS and Spatial Analysis in Archaeology, University College London, Ph.D., Archaeology, McGill University

Currently Associate Professor of Anthropology, University of Colorado Colorado Springs. I took my first modelling class in Repast with Dr. Mark Lake as part of my M. Sc. at UCL. After a workshop with Dr. Luke Premo and Dr. Anne Kandler, I moved to NetLogo and haven’t looked back.

Find our recent textbook, Agent-based modeling for Archaeology: Simulating the Complexity of Societies here: https://santafeinstitute.github.io/ABMA/

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.