2007-Present

My lab's page for this project can be found here.

Our goal with CAGE is to provide a simple, yet general and robust, engine for the creation of cultural training, analysis, and simulation games. Filling in the application portion of the CARA umbrella project, CAGE-based games leverage a number of other technologies provided by the LCCD.

The motivation for CAGE arises from the need to effectively visualize large datasets. A number of LCCD projects (e.g., SOMA, CONVEX) use real-world data to predict how a geopolitical actor will act, given some hypothetical world state. Both the input and output data from these projects are huge, and not easily deciphered by a human user. Exploring these data through a virtual world environment can help alleviate this problem.

We are currently on the fourth iteration of CAGE-based games. Each application is aimed at a different user base, but shares much of the same underlying technology. At its heart, each game provides a method for its user to explore and interact with a hypothetical world containing one or more of the roughly eighty geopolitical actors the LCCD currently tracks.

WebCAGE v2 (2010): This iteration of CAGE serves as the "immersive virtual world" successor to the initial WebCAGE. Science magazine does a great job explaining our work!

WebCAGE (2009): WebCAGE is aimed at the seasoned policy analyst interested in seeing how policy changes (e.g., stopping NGO support, legalizing a group, opening negotiations) will affect opposing actor responses (e.g., bombings, kidnappings) over an extending time period. The game itself focuses more on visualizing large datasets than creation of an immersive virtual world. As the name implies, this game is entirely available online.

SAGE (2008): SAGE's target audience is the "newbie" policy analyst. We provide a 3D environment in which the user interacts with a significantly smaller subset of groups, actions, and environmental variables than in WebCAGE. By making changes to the hypothetical world in which these groups exist, the user discerns affects of policy changes.

CAGE (2007): CAGE, our initial Cultural Island Game (CIG), exists as a simulation on a private island in the Second Life virtual world. In an Afghan village, a United States soldier must interact with residents ranging from the revered village elders to regular farmers. This game was built as a training simulation to reduce culture shock and prevent acting against societal norms.

Although the lab tends to track groups our sponsors find interesting (terrorist organizations), CAGE and the related predictive technologies found in engines like SOMA and CONVEX are theoretically proven to work on any data source. We are beginning to explore other, unrelated realms like disease tracking, and will post results as they manifest!

For additional information, please contact Dr. V.S. Subrahmanian.

My lab's page for this project can be found here.

V.S. Subrahmanian and John Dickerson. What Can Virtual Worlds and Games do for National Security? Science, vol. 326, pp. 1201-02. 27 November 2009.

J. Dickerson, M. Martinez, D. Reforgiato, V.S. Subrahmanian. CIG: Cultural Islands and Games. Proc. 2008 International Conference on Computational Cultural Dynamics. AAAI Press, Menlo Park, CA, 2008, pp. 26-31.

This research was funded in part by the Air Force Office of Scientific Research (AFOSR), the Naval Research Laboratory (NRL), the Army Research Office (ARO), the National Science Foundation (NSF), the University of Maryland (UMD), and other sources.