Monday, September 26, 2011

Advanced GeoSimulation Models

Advanced GeoSimulation Models edited by Danielle Marceau and Itzhak Benenson brings together a number of authors that highlight the the frontier in geosimulation in particular, and in cellular automata and agent-based modelling in general.

Click here to see the forward by Mike Batty.

We have a chapter in the book entitled "Advances and Techniques for Building 3D Agent-Based Models for Urban Systems" Belwo you can read the abstract of the chapter along with see some of our figures.

There is a growing interest in relating agent-based models to real-world locations by combining them with geographical information systems (GIS) which can be seen with the increase of geosimulation models in recent years. This coincides with the proliferation of digital data both in the two and three dimensions allowing one to construct detailed and extensive feature-rich and highly visual 3D city models. This chapter explores some of these developments in relation to our own initial work on building 3D geospatial agent-based models of urban systems and the technologies that allow for such models to be created. These range from coupling agent-based models with 3D visualizati on, to building 3D agent-based models in 3D animation and rendering packages, and to using 3D virtual worlds for the creation of agent-based models.

The  Swiss  Re  building  and  the  City  of  London  imported  into  the  Crysis  game  engine.

Full Reference:
Crooks, A. T., Hudson-Smith, A. and Patel, A. (2011), Advances and Techniques for Building 3D Agent-Based Models for Urban Systems, in Marceau D. and Benenson, I. (eds.), Advanced Geosimulation Models, Bentham Science Publishers, Hilversum, The Netherlands, pp 49-65.(pdf

Monday, September 19, 2011

An agent-based model of the housing market

Why agent-based modeling? In the interview below  Doyne Farmer discuses his work with Rob Axtell and John Geanakoplos, who aim to create an agent-based model of the U.S. economy that will people make better understand past, and future, financial crises.

But going back to the question above, why agents? to quote from the SFI website: "Whereas a traditional economic model makes future predictions based on past market behavior and thus fails in unprecedented situations, their agent-based model takes into account the actions of individual decision makers, assigning behavioral rules to each agent in the model"