Wednesday, December 21, 2016

A semester with CSS

This last semester I gave both a graduate and undergraduate course in Computational Social Science (CSS). Both courses survey computational approaches such as system dynamics, social network analysis, machine learning, cellular automata, discrete event simulation, agent-based modeling, and microsimulation to study social phenomena with emphasis on complexity theory.

For the undergraduate class, we met twice a week. In the first class of each week I would outline the topic,  discuss a specific modeling approach and give a range of sample applications. While the second class of the week was devoted to hands on model development (I chose to use NetLogo for this), in order to cement what was discussed in the first class (a learning by doing if you like.). For example, one week we discussed cellular automata (CA) modeling, where in the first class, I outlined its evolution, its basic proprieties and applications (e.g. from simple voting models to that of urban growth). In the second class, the students then built a CA model from scratch.  For the graduate class, more emphasis was placed on theory, critiques of modeling and discussion of key texts.

In both classes, all the students needed to carry out a project where they develop a computational model that investigates a social science research question. This exercise is often their first model (especially for the undergraduates) that many students ever create. Below you can see some of this years models.

Thursday, December 01, 2016

International Congress on Agent Computing

Between the 29th and 30th of November, the International Congress on Agent Computing was held at George Mason University. It was organized to celebrate the 20th anniversary of the publication of Growing Artificial Societies by Robert Axtell and Joshua Epstein. The congress brought together a great line up of interdisciplinary keynote speakers: Brian Arthur, Mike Batty, Stuart Kauffman and  David Krakauer and a  panel discussion entitled "Barriers to Progress in Agent Computing—Technical and Social" with Chris Barrett, Steven Kimbrough, Blake LeBaron, Dawn ParkerFlaminio Squazzoni and Leigh Tesfatsion. Along with the keynotes and there panel there were also over 19 posters and 59 presentations which showcased and demonstrated the theme of the congress, that of the:
"explosive growth of agent modeling over the past two decades in the social sciences, in business and government, and related areas, and offer a tour d’horizon of its present state and myriad applications. Looking forward, we will identify challenges and opportunities — Hilbert Problems, if you will — to shape the future of agent-based computational modeling."

Joshua Epstein and Robert Axtell presenting their works.

Josh and Rob each gave really impressive talks entitled “Agent-­based modeling: From Napkins to Nations” and "The Adoption of Agent Computing over Time by Social Scientists as Compared to Game Theory and Experimental/ Behavioral Economics" respectively. Which reflected how agent computing has evolved over the last 20 years with plenty of funny anecdotes along the way including references and critiques of their works such as "masculine gods of their cyberspace creations" and where the field is going.

What really impressed me about the congress was the atmosphere. That of like minded individuals from many different disciplines coming together and discussing agent computing, complexity and modeling more generally.  Some of this can be seen via photos and tweets of the event.

Alison Heppenstall, Nick Malleson and myslef also participated at the congress with a talk entitled "ABM for Simulating Spatial Systems: How are we doing?" which assessed how has agent-based modeling within the geographical sciences advanced over the last 20 years. Below one can read a brief outline of the talk and a movie of presentation.

While great advances in modeling have been made, one of the greatest challenges we face is that of understanding human behavior and how people perceive and behave in physical spaces. Can new sources of data (i.e. “big data”) be used to explore the connections between people and places?   In this paper we will review of the current state of art of modeling geographical systems.  We highlight the challenges and opportunities through a series of examples that new data can be used to better understand and simulate how individuals behave within geographical systems.

Key Words: Agent-based Modeling, Geographical Information Science, Networks, Cities, Geographical Systems.

Heppenstall, A., Crooks A.T. and Malleson, N. (2016), ABM for Simulating Spatial Systems: How are we doing? International Congress on Agent Computing, 29th-30th, November, Fairfax, VA.

The Growth of Geographical  ABM (selected examples).