Tuesday, June 28, 2016

Spatial Agent-based Models of Human-Environment Interactions: Spring 2016

During the past spring semester I taught a class entitled "Spatial Agent-based Models of Human-Environment Interactions". As with many of my courses, students were expected to complete a end of semester project, in this case, develop an agent-based model that explores some aspect of related to the course theme of human-environment interactions. Below is a selection of these projects, which ranged from hiking along the Application trail,  to that of exploring the ride-sharing economy, to the spread of diseases, ecosystem recovery modeling and the origins of social complexity. 


I would like to thank the Students of CSS 645: Spatial Agent-based Models of Human-Environment Interactions for their participation in the class.


Wednesday, June 22, 2016

The Geography of Conflict Diamonds: The Case of Sierra Leone

At the forthcoming  2016 International Conference on Social Computing, Behavioral-Cultural Modeling, and  Prediction and Behavior Representation in Modeling and Simulation. we will be presenting a paper is entitled "The Geography of Conflict Diamonds: The Case of Sierra Leone" The abstract and some of the figures from the paper are below. At the bottom of the post you can find the full reference and a link to the paper and model.
In the early 1990s, Sierra Leone entered into nearly 10 years of civil war. The ease of accessibility to the country's diamonds is said to have provided the funding needed to sustain the insurgency over the years. According to Le Billon, the spatial dispersion of a resource is a major defining feature of a war. Using geographic information systems to create a realistic landscape and theory to ground agent behavior, an agent-based model is developed to explore Le Billon's claim. Different scenarios are explored as the diamond mines are made secure and the mining areas are moved from rural areas to the capital. It is found that unexpected consequences can come from minimally increasing security when the mining sites are in rural regions, potentially displacing conflict rather than removing it. On the other hand, minimal security may be sufficient to prevent conflict when resources are found in the city.

Motives and action-guiding motive via the Intensity Analyzer

A visual comparison of model results to actual events. a: Average model results using default parameter values. b: Actual event intensity.




Full Reference:
Pires, B. and Crooks, A.T. (2016), The Geography of Conflict Diamonds: The Case of Sierra Leone, in Xu, K. S., Reitter, D., Lee, D. and Osgood, N. (eds.), Proceedings of the 2016 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, Washington, DC, pp. 335-345. (pdf)
A full description of the model and source code along with the data is available at: https://www.openabm.org/model/4955/