SBIR-STTR Award

Today’s contemporary operating environment is filled with individuals and crowds that have become a tactical asset to the enemy. When confronted by crowds, soldiers face the ambiguity of not knowing who is friend or foe and likely don’t possess the requisite cross-cultural communication skills to adequately respond to the rapidly changing threat. Poor choices result in escalation of hostility threatening lives and the mission. Learning appropriate skills to deal with individual and group behaviors is an imperative; and a variety of game-based technologies show promise to close the training gap. Forterra and Charles River Associates propose to research game technologies and crowd modeling approaches that can be integrated to produce an appropriate virtual training system. We propose to analyze the behaviors of crowds to understand their dynamics then to look at available cognitive modeling architectures. We’ll look at several game based platforms to find an appropriate match to support virtual training with large numbers of avatars in an asymmetric warfare environment. A feasibility demonstration is proposed as a culminating event. Emphasis will be placed on solutions than can be commercialized to support similar training needs in combat medicine and emergency preparedness.

Keywords:
Mmog Crowds Models Cognitive Behaviors Games

Today’s contemporary operating environment is filled with individuals and crowds that are tactical assets to adversaries. When confronted by crowds, soldiers face the ambiguity of identifying who is friend or foe, and likely don’t possess the requisite cross-cultural communication skills to adequately respond to rapidly changing threats. Poor choices result in escalation of hostility threatening lives and the mission. Learning appropriate skills to deal with individual and group behaviors is imperative; and a range of game-based technologies show promise to close the training gap. Forterra and Charles River Analytics propose to integrate game technologies and crowd modeling approaches to produce a highly scalable virtual training system suitable for the COE. We propose to build from Phase I efforts that analyzed architectures and capabilities of various technologies and to implement a working prototype system that will support distributed virtual training with large numbers of synthetic and virtual avatars in an asymmetric warfare environment. A feasibility demonstration will be performed as a culminating event and a non-proprietary application programmer’s interface will be published. Emphasis will be placed on solutions than can be commercialized to support similar training needs in combat medicine, emergency preparedness, and related corporate training exercises.

Keywords:
Avatar Virtual World Simulation Training Crowds Ai Gaming