Notice and Invitation
Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Social Science
Department of Computational and Data Sciences
College of Science
George Mason University
Bachelor of Science, Lake Superior State University, 2004
Master of Science, George Washington University, 2006
REALLAND: A WARGAMING APPROACH TO
COMPUTATIONAL INTERNATIONAL RELATIONS
Tuesday, December 5, 1:00 p.m.
Research Hall, Room 92
All are invited to attend.
Claudio Cioffi-Revilla, Dissertation Director
The objective of this study is to advance a wargaming approach to computational international relations (IR). Wargaming has a long tradition of artfully balancing between realism and human playability. Those same techniques can be incorporated into computational IR models. A wargaming approach affords both greater resolution in the operational environment and emulation of human decision-making, which provides a significant alternative to past computational IR models of international conflict. As a demonstration of this approach, I developed two simulations: Basic and Enhanced RealLand.
Basic RealLand is a replication of the work of past researchers (Cusack and Stoll, 1990; Duffy, 1992) providing a comparative foundation for innovation within Enhanced RealLand. Enhanced RealLand combines computational social science (CSS) techniques with defense and commercial wargaming mechanisms to enable a wargaming approach to computational IR. It is a strategic-operational simulation where players sense the world, identify issues, develop strategies, and implement actions such as trade, alliance building, and war. The shift away from game-theoretic approaches for modeling computer agents as nation-states to the conflict-theory model as players proved promising, and the results generate a world worthy of the prominent IR realist theorists. An important contribution is the creation of a pseudo history, similar to that of a narrative resulting from a social simulation.
This study advanced a wargaming approach to computational IR by demonstrating that additional representative modeling, in a human playable form, can be used for advanced IR research. By placing the focus on simulating human decision-making through a descriptive process, Enhanced RealLand provides an approach and extensible framework for computational IR models to have analytic utility whether for theorists, policy-makers, or educators.
A copy of Karl’s dissertation is available for examination from Karen Underwood, Department of Computational and Data Sciences, 373 Research Hall. The dissertation is available to read only within the Department and cannot be taken out of the Department or copied.