Community

jcorrean Member since: Sunday, August 26, 2012

Licensure in Psychology, Master in Behavioral Research Methods, PhD Student in Science

Evolution of social behavior and complex systems

Firouzeh Taghikhah Member since: Monday, November 18, 2019 Full Member

  • System modelling of behavior change
  • Socio-environmental systems for sustainable development
  • Life cycle analysis
  • Serious games for sustainable future
  • Food preferences
  • Agricultural economics

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.

Vinicius Ferraz Member since: Monday, March 01, 2021 Full Member

Game theory, artificial intelligence, agent-based models, genetic algorithms.

Shelby Manney Member since: Friday, September 26, 2014

BA - English, BS - Anthropology (Archaeoinformatics - GIS, Applied Stats, Data Mang.,CRM CERT), BFA - Music, BA - Writing & Rhetoric, MA - Technical, Professional, & Science Writing (TPSW - Cert), MS - Cultural Studies in Applied Sciences (Philosophy of Science - Archaeology/Semiotics Focus), MA - Anthropology

General Question:
Without Central Control is self organization possible?

Specific Case:

Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?

Yutaka Nakai Member since: Sunday, January 19, 2014

Ph.D.

ABM researches on the theory of social systems. For example, the formation of a community, the origin of politics, nation, and state.

Boyan Vassilev Member since: Friday, August 26, 2016

MA

I’m a trained philosopher, but, besides conceptual problems, I care for conclusions based on systematic observations and I also care for the applicability of those conclusions. One might say that I wish I were a behavioral economist, or maybe an ethologist/behavioral ecologist.

Tom Briggs Member since: Tuesday, December 13, 2016 Full Member Reviewer

MPS, Industrial/Organizational Psychology, BA, Psychology

PhD Student, Computational Social Science
Department of Computational and Data Sciences
George Mason University
Fairfax, VA, USA

I use ABM to study organizations, leadership, employee behavior and performance, and the social/psychological theories addressing workplace behavior and outcomes.

I have also used ABM to explore mass violence, active shooters, and mass shootings, including the spread of mass violence and its antecedents.

Arpan Jani Member since: Monday, September 30, 2019

Arpan Jani received his PhD in Business Administration from the University of Minnesota in 2005. He is currently an Associate Professor in the Department of Computer Science and Information Systems at the University of Wisconsin – River Falls. His current research interests include agent-based modeling, information systems and decision support, behavioral ethics, and judgment & decision making under conditions of risk and uncertainty.

agent-based modeling; behavioral ethics; information systems and decision support; project management; judgment & decision making under conditions of risk and uncertainty.

Brent Auble Member since: Friday, December 17, 2010

B.S. Computer Science, Lafayette College, MAIS, Computational Social Science, George Mason University

Dissertation: Narrative Generation for Agent-Based Models

Abstract: This dissertation proposes a four-level framework for thinking about having agent-based models (ABM) generate narrative describing their behavior, and then provides examples of models that generate narrative at each of those levels. In addition, “interesting” agents are identified in order to direct the attention of researchers to the narratives most likely to be worth spending their time reviewing. The focus is on developing techniques for generating narrative based on agent actions and behavior, on techniques for generating narrative describing aggregate model behavior, and on techniques for identifying “interesting” agents. Examples of each of these techniques are provided in two different ABMs, Zero-Intelligence Traders (Gode & Sunder, 1993, 1997) and Sugarscape (Epstein & Axtell, 1996).

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.