Matthew Oldham Member since: Friday, June 17, 2016

Bachelor of Economics (tons), MAIS - Computational Social Science

I am a Ph.D. candidate in Computational Social Science (CSS) program at George Mason (GMU). I hold a MAIS from GMU and a Bachelor of Economics from the University of Tasmania. My research interests are the application of ABMs, network analysis, and machine learning to financial markets. My email address and website is [email protected] and

I am interested in using agent-based model to understand the behavior of financial markets

Smarzhevskiy Ivan Member since: Sunday, August 17, 2014 Full Member Reviewer

Associate professor of chair of economics and mathematical methods

decision making, agent based models

Matteo Richiardi Member since: Wednesday, February 01, 2017


Matteo Richiardi is an internationally recognised scholar in  micro-simulation modelling (this includes dynamic microsimulations and agent-based modelling). His work on micro-simulations involves both methodological research on estimation and validation techniques, and applications to the analysis of distributional outcomes, the functioning of the labour market and welfare systems. He is Chief Editor of the International Journal of Microsimulation. Examples of his work are the two recent books “Elements of Agent-based Computational Economics”, published by Cambridge University Press (2016), and “The political economy of work security and flexibility: Italy in comparative perspective”, published by Policy Press (2012).

Robert Canales Member since: Tuesday, October 22, 2013

Environmental Engineering, PhD, Statistics, MS

I use agent-based systems, stochastic process, mass balance models and computational statistics in exploring human exposure assessment.

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).

amoozgar Member since: Wednesday, February 01, 2012

B.S. Computer Science

AI, Agent based modeling and Social Simulation

Daniel Formolo Member since: Friday, June 10, 2016

PhD Student

PhD student in the Agent Systems Research Group of the Department of Artificial Intelligence at the VU University Amsterdam. Current research focuses on Modeling Human Behavior and exploring Serious Games interactions with humans.

Beth Fulton Member since: Thursday, January 12, 2012 Full Member Reviewer


Using agent based models to look at ecosystem-based or integrated management of oceans and coastal zones

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