The Mason Gazette just came out with a good article on Professor Robert Axtell and Agent-Based Modeling:
Axtell is one of the leaders in this field of research. In 1996, Axtell cowrote a seminal work on artificial societies titled “Growing Artificial Societies: Social Science from the Bottom Up,” with Joshua Epstein of the Brookings Institution. In the book, Axtell and Epstein present a computer model with which they begin to develop a bottom-up social science in a land known as Sugarscape.
As various changes in environment or agents are introduced, data on differing outcomes are produced. What the authors found is that “fundamental collective behaviors such as group formation, cultural transmission, combat and trade are seen to emerge from the interaction of individual agents following a few simple rules.”
Currently, there are three main areas where multiagent systems modeling affects policy: traffic; propagation of disease, particularly since Sept. 11, 2001; and military tactics. Axtell says that teaching MBA students to build models of entire companies with these agent-based techniques is definitely on the horizon. Using this type of modeling to address institutional dilemmas could one day help corporations analyze problems and determine more effective solutions than might have been possible in the past.
“Our models essentially enhance the equation-based methodology (EBM), which is, in a manner of speaking, the forerunner of the modeling we do,” Axtell says. “But EBM misses all the action around the average, and, in some cases, that action matters a lot. Predicting extreme events is what’s most important.”
I took Dr. Axtell's Agent-Based Modeling class this past semester and must say it was one of the most interesting and thought-provoking classes I have taken thus far in my PhD program. I enjoyed it so much I am now taking an intro to computer science course this summer to learn better programming skills to use agent-based models in my research.
For any of my fellow PhD students at GMU, I cannot recommend Dr. Axtell's class highly enough. I also recommend Eric Beinhocker's excellent book, The Origin of Wealth, as a good layman's introduction to many of the concepts we covered in the class. (Download chapter 1 here. [PDF])
Here is a PowerPoint presentation I gave on The Origin of Wealth giving a brief overview of the breadth of topics covered in the book:
The agent-based modeling approach strikes me as a much fuller and richer way to model human behavior than traditional mathematical analysis. When I was working as an engineer, I got invovled with doing Monte Carlo simulations to analyze material failure in steam turbines. Agents are an even more powerful tool for social science research that allow the modeling of heterogeneity of individuals, randomness of events, congnitive limitations, social influence of neighbors, etc. in a way that conventional analysis cannot address. Professor Larry Iannaccone and Michael Makowsky have even used this approach to model the effects of religious commitment.
If you can't tell, I'm very excited by the development of these tools and hope to make them a big part of my analytical toolkit.
See my previous post on complexity economics.
(HT Pete Boettke)
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