Crime and Slums

This project focuses on the emergence of criminal activity due to the unmet human needs of those living in Rio's favelas. An agent-based model is developed to explore how human needs, environmental factors, and individual attributes impact state-level behaviors. The emergence of organized crime is observed as "common" criminals turn into gang members. The prevention of conflict requires policies that anticipate responses and avoid conflict. By "re-creating" the current environment, we have the ability to potentially predict the onset of violence where it does not yet exist or understand the source of conflict in those areas already in the midst of violence.

Selected outputs from this research: 

Pint, B., Crooks, A. T., and Geller, A. (2010), An Agent-based Model of Organized Crime: Favelas and the Drug Trade. 2nd Brazilian Workshop on Social Simulation, Sao Bernardo do Campo, Brazil. (pdf)

50 Facts about Agent-Based Computing

I just found out about an interesting pamphlet entitled " 50 Facts about Agent-Based Computing" by Michael Luck and thought it was worth sharing. The pdf can be downloaded from here.

Urban Modelling: Algorithms, Calibrations, Predictions

Mike Batty of CASA "Urban Modelling: Algorithms, Calibrations, Predictions" which was originally published in 1976 has been republished by popular demand!

The book covers a plethora of topics, introducing the reader to simulation models and the need for such methods. For example, "simulation methods are used to derive the behaviour of the system when the system is too complex to be modelled using the more direct analytic approach (Batty, 1976)."

The book provides a summary of the first generation of urban models referring to the key authors and models such as Lowry (1964) model and it successor including the Pittsburgh Time-Oriented Metropolitan Model (TOMM), the Projective Land Use Model (PLUM) for the San Francisco area, and a wide variety of Activity Allocation and Stocks-Activities models. The book presents how such models were mainly developed for practical planning situations through metropolitan planning agencies or consultants in North America and in several European cities. How at first, these models where developed with the aim of solving land-use and transportation questions, later being employed to address a wider range of urban problems.

Anyone interested in urban modelling and spatial interaction models is recommended to explore this book.

Reference:
Lowry, I.S. (1964), A Model of Metropolis, Rand Corporation, Santa Monica, CA.

Agent Analyst Bird Migration Model

While I have blogged about Agent Analyst before (see here), the Redlands Institute have created some movies showing a simulation of bird migration patterns. While the exact details are not abundant, it appears they where developed to learn and demonstrate concepts relating to linking agent-based models with a GIS. Specifically using the Agent Analyst toolkit with Tracking Analyst in ArcMap (as shown in the movie below):

While this movie shows a live model run:


Finally the movie below shows how one can visualize the results in ESRI's ArcGlobe.



More movies from the Redlands Institute on YouTube can be found here.

Cormas and ComMod

Following on from the UVA Bay Game post I thought it was about time to blog about Cormas and the ComMod (Companion Modeling Approach) which focus on participatory agent-based modeling for resource management.

Why the interest? Take ecosystem management as an example, there are often many actors (stakeholders) who influence and control ecosystem management. For example, in the Chesapeake Bay there are farmers, local policy-makers, watermen, and developers. Such stakeholders have many different goals, associated feedbacks, negotiations etc... The question is how does one build models of such interactions?

Often when we build models of such interactions we do not always engage with stakeholders directly. Participatory modeling approaches such as companion modeling offers one way for such engagement. It uses various techniques, including role playing games in the sense that models are built with the direct involvement of stakeholders. Where modelers develop and validate model rules in conjunction with those one is modeling. Such a direct involvement of stakeholders focuses our attention on how decisions are made and what are the problems rather than just simulating the effects (e.g. Gimblett et al., 2002).

This brings me back to the ComMod approach and Cormas (an agent-based simulation framework, often used in conjunction with the ComMod approach). In the sense that ComMod is a iterative modeling process from the “bottom up.” ComMod provides an endless cycle of "field work and data analysis -> role playing games -> agent-based model development and implementation -> simulation -> field work again (Barreteau, 2003) as depicted below:

Some references for further reading:

• Barreteau, F.O. and others (2003), 'Our Companion Modelling Approach', Journal of Artificial Societies and Social Simulation, 6(1), Available at http://jasss.soc.surrey.ac.uk/6/2/1.html.
• Etienne, M. (2003), 'SYLVOPAST: A Multiple Target Role-Playing Game to Assess Negotiation Processes in Sylvopastoral Management Planning', Journal of Artificial Societies and Social Simulation, 6(2), Available at http://jasss.soc.surrey.ac.uk/6/2/5.html.
• Gilbert, N., Maltby, S. and Asakawa, T. (2002), 'Participatory Simulations for Developing Scenarios in Environmental Resource Management', in Urban, C. (ed.), Third Workshop on Agent-Based Simulation, SCS European Publishing House, Passau, Germany, pp. 67-72.
• Ramanath, A.M. and Gilbert, N. (2004), 'The Design of Participatory Agent-Based Social Simulations', Journal of Artificial Societies and Social Simulation, 7(4), Available at http://jasss.soc.surrey.ac.uk/7/4/1.html.

To see some Cormas examples (Click here). Click here to see the ComMod program at work and here for the ComMod site. While the movie below shows one application of Cormas: