VirThai: A PS-I Implemented Agent-Based Model of Thailand as a Predictive and Analytic Tool

Brandon Alcorn, Miguel Garces, Allen Hicken

In this paper we report on the deployment of “VirThai,” a virtualization type agent-based model of contemporary Thailand, to produce predictions for events of political and policy interest over the course of 2011. Predictions are inferred from distributions of outcomes across large batches of counterfactual futures. We will assess the performance of the model as a forecasting tool, as a technique for understanding the mechanisms that drive political outcomes, and as a means for stimulating new insights or lines of reasoning among country experts.

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UPDATE: This paper has since been published in the 12th volume of the Stanford Journal of East Asian Affairs. Download Here

Forecasting Political Futures For Thailand: Leveraging Social Science Theory in a Virtualization Model

Ian Lustick, Roy Eidelson, Matthew Tubin, Brandon Alcorn, Miguel Garces

This poster was presented at “HSCB Focus 2011: Integrating Social Science Theory and Analytic Methods for Operational Use“.

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From the website, the purpose of this meeting was to “showcase research and applications in the general HSCB modeling area and to engage OSD HSCB Modeling Program personnel as well as leading scientific and technical experts working in HSCB related fields in a technical exchange. A specific focus of this conference will be to promote communication between the development and user communities and to facilitate the transition of HSCB capabilities into operational use. In addition to personnel from the OSD HSCB Modeling Program, representatives from both DoD and other Government agencies are expected to attend and showcase their programs in this area.  Researchers and developers from industry, academia, and government labs, including current HSCB program awardees, are invited to present their work and ideas related to HSCB technologies. Additionally, representatives from end-user communities within DOD and elsewhere in the US government are strongly encouraged to present requirements, use cases, and challenge problems to the community.”

From Theory to Simulation: The Dynamic Political Hierarchy in Country Virtualization Models


Ian Lustick, Brandon Alcorn, Miguel Garces, Alicia Ruvinsky

This paper suggests that computer-assisted agent-based modeling has the ability to move beyond abstract representations of political problems to theoretically sound virtualizations of real-world polities capable of producing probabilistic forecasts from distributions of stochastically perturbed model trajectories. In contrast to statistical approaches, this technique encompasses both prediction and explanation, with every distinctive trajectory traceable backward from the occurrence or non-occurrence of an event of interest through the branching points and mechanisms that led to it. In this paper we illustrate our technique for building a country-scale model from corroborated theories, focusing on the “Dynamic Political Hierarchy” module that integrates theories of cross-cutting cleavages, nested institutions, and dynamic loyalties. We present our forecasts for significant political events in Thailand for the year August 2010-July 2011. Drawing on this case we demonstrate how the challenges of internal validity can be met in complex formal models and conclude by emphasizing the importance of advances in visualization techniques for parsing large amounts of interrelated time-series data.

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UPDATE: This paper has since been published in Volume 24 Number 3 of the Journal of Experimental & Theoretical Artificial IntelligenceDownload Here

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