Agent-Based Models of Crowd Behaviuor

Agent-based modelling allows us to model individuals and how these individuals interact to form emergent phenomena. A great example of this is crowds. Recently we (people at CASA) have been exploring ways to carryout pedestrian agent-based models in 3D and I just came across this short presentation by Paul Torrens entitled “Modelling Crowd Behaviour” from the O'Reilly Where 2.0 Conference. It is worth watching the talk (15min) as it shows how GIS and ABM can be coupled together and why studying crowd movement is important.

The talk can be watched here.

If you interested in pedestrian modelling and software the papers by Christian Castle might be of interest:

Castle, C.J.E. (2007), Guidelines for Assessing Pedestrian Evacuation Software Applications, Centre for Advanced Spatial Analysis (University College London): Working Paper 115, London.

Castle, C.J.E. and Longley, P.A. (2008), 'Emergency Pedestrian Evacuation Analysis: A Review and Interpretation of Software Applications', in Sui, D.Z. and Cutter, S.L. (eds.), Geospatial Technologies and Homeland Security: Research Frontiers and Challenges, Springer, Berlin.

Agent-Based Crime Simulation

I just come across a blog called “Agent-Based Crime Simulation” by Nick Malleson who is building an agent-based model to predict rates of residential burglary. Within the model potential burglars are represented as agents, drawing from studies in criminology and artificial intelligence. The virtual environment is made as realistic as possible by incorporating GIS data (in the form of OS Mastermap) for the area of study.

While the model is still only a prototype, it is one of the first examples I seen using GIS in Repast Simphony, he has also posted a short video showing simple burglar agents moving around their environment.

For more information about the model and Nick's blog see “http://crimesim.blogspot.com/”.

Video from Agent-Based Crime Simulation.

GIS Extension for NetLogo

I am a big fan of NetLogo, I have seen many examples and have been wondering how I could easily create agent-based models using GIS within it. Whilst browsing the OpenABM website I came across a post by Eric Russell about a beta version GIS Extension for NetLogo and could not resist trying it out. The extension provides primitives for importing vector GIS data (in the form of ESRI shapefiles) and raster GIS data (in the form of ESRI ascii grid files) into NetLogo.

The extension and instillation instructions can be downloaded from:
http://ccl.northwestern.edu/netlogo/4.0/extensions/gis/

There are two example models, one which loads a raster file of surface elevation for a small area near Cincinnati, Ohio (above). To quote from the documentation:

 “It uses a combination of the gis:convolve primitive and simple NetLogo code to compute the slope (vertical angle) and aspect (horizontal angle) of the earth surface using the surface elevation data. Then it simulates raindrops flowing downhill over that surface by having turtles constantly reorient themselves in the direction of the aspect while moving forward at a constant rate”.

The second example model (below) loads four different GIS datasets: a point file of world cities, a polyline file of world rivers, a polygon file of countries, and a raster file of surface elevation. It provides a collection of different ways to display and query the data, to demonstrate the capabilities of the GIS extension.

Geographically Explicit Agents

A quick post for anyone interested following on from a presentation that I gave Association of American Geographers (AAG) Annual Meeting in Boston entitled “Using geographically explicit agents to explain and explore urban phenomena” given in the Agent Based Modeling II session

The Abstract of the talk was as follows:

"Agent-based modelling is at the forefront of computer modelling research focusing on the individual or groups of individuals, and how these individuals interact to form emergent structures. In particular, the ABM paradigm is becoming an increasingly used technique to study cities and regions. However, this new paradigm poses many challenges with regard to modelling. These include but are not limited to: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the way the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. 

This paper will explore how we are addressing these issues with illustrated examples (applications) specifically focusing on residential segregation dimensioned upon London, which the author has developed and is currently developing. Furthermore, the models address other major problems with respect to agent-based modelling specifically integrating GIS within such models via a loose coupling approach. This integration of spatial data adds extra levels of complexity when studying urban phenomena, specifically that of segregation within agent-based models which is hardly touched upon in the literature. Furthermore, this integration allows the models to be grounded in actual places where geometrical features restrict agent interactions and how such places change over time. The paper will conclude with highlighting future avenues of research."

 

The presentation can be downloaded from here and a new working paper entitled “Constructing and Implementing an Agent-Based Model of Residential Segregation through Vector GIS” which slightly mirrors the talk can be found here. The full reference for this paper is:

Crooks, A. T. (2008), Constructing and Implementing an Agent-Based Model of Residential Segregation through Vector GIS, Centre for Advanced Spatial Analysis (University College London), Working Paper 133, London.

While the presentation focuses mainly on the second half of the abstract due to time constraints, further information about the challenges agent-based modelling poses with regard to modelling can be found in the following working paper:

Crooks, A. T., Castle, C. J .E. and Batty, M. (2007), Key Challenges in Agent-Based Modelling for Geo-Spatial Simulation, Centre for Advanced Spatial Analysis (University College London), Working Paper 121, London.

As always any thoughts or comments about the work or presentation are more than welcome.

New Working Paper: ABM of Residential Segregation

We just finished a new working paper entitled “Constructing and Implementing an Agent-Based Model of Residential Segregation through Vector GIS”

The abstract is as follows:

In this paper, we present a geographically explicit agent-based model, loosely coupled with vector GIS, which explicitly captures and uses geometrical data and socio economic attributes in the simulation process. The ability to represent the urban environment as a series of points, line and polygons not only allows one to represent a range of different sized features such as houses or larger areas portrayed as the urban environment but is a move away from many agent-based models utilising GIS which are rooted in grid-based structures. We apply this model to the study of residential segregation, specifically creating a Schelling (1971, 1978) type of model within a hypothetical cityscape, thus demonstrating how this approach can be used for linking vector-based GIS and agent-based modelling. A selection of simulation experiments are presented, highlighting the inner workings of the model and how aggregate patterns of segregation can emerge from the mild tastes and preferences of individual agents interacting locally over time. Furthermore, the paper suggests how this model could be extended and demonstrates the importance of explicit geographical space in the modelling process.

Keywords: Agent-Based Modelling, GIS, Residential Segregation, Repast

The full reference is:

Crooks, A. T. (2008), Constructing and Implementing an Agent-Based Model of Residential Segregation through Vector GIS, Centre for Advanced Spatial Analysis (University College London): Working Paper 133, London, England. (pdf)

The paper can be downloaded from here. As always, any thoughts or comments about the paper are more than welcome.