Military Embedded Systems

Army-funded research focuses on AI teaming to dynamically complete tasks


April 05, 2019

Mariana Iriarte

Technology Editor

Military Embedded Systems

Army-funded research focuses on AI teaming to dynamically complete tasks
Army graphic

ABERDEEN, Md. University and Army Research Laboratory (ARL) scientists published a new research paper in Science Advances that looks at soldier brain activity during specific tasks for ways to incorporate artificial intelligence (AI) teaming to dynamically complete tasks.

Dr. Jean Vettel, a senior neuroscientist at the Combat Capabilities Development Command Army Research Laboratory, also known as ARL, stated in an Army release, that the Army is looking to create technologies that can predict states and behaviors of the individual to create a more optimized team.

Recent collaborative work between ARL and the University at Buffalo is looking at ways the dynamics and architecture of the human brain may be coordinated to predict such behaviors and consequently optimize team performance.

"While this research focuses on a single person, the purpose is to understand how an individual's brain activity can be used to create novel strategies for a teaming environment, both for teams with Soldiers as well as teams with Autonomy" states Vettel, a co-author of the recent paper.

"In military operations, Soldiers perform multiple tasks at once. They're analyzing information from multiple sources, navigating environments while simultaneously assessing threats, sharing situational awareness, and communicating with a distributed team. This requires Soldiers to constantly switch among these tasks, which means that the brain is also rapidly shifting among the different brain regions needed for these different tasks," Vettel adds. "If we can use brain data in the moment to indicate what task they're doing, AI could dynamically respond and adapt to assist the Soldier in completing the task."

Researchers first sought to understand how the brain coordinates its different regions while executing a particular task. They used a computational approach to understand how this may be characterized to inform the behavioral prediction. To complete the study, researchers mapped how different regions of the brain were connected to one another in 30 different people via tracts of tissue called white matter.

Next, the scientists converted these maps into computational models of each subject's brain, and used computers to simulate what would happen when a single region of a person's brain was stimulated. The researchers then used a mathematical framework, which they developed, to measure how brain activity became synchronized across various cognitive systems in the simulations.

Dr. Kanika Bansal, lead author on the work, points out the method described in the work could potentially be extended outside the brain, as well, creating dynamic teaming assignments in the future.

This research was a collaboration between UB, ARL, Columbia University, the University of Pennsylvania, Carnegie Mellon University and the University of California, Santa Barbara. Other authors include Sarah F. Muldoon, University at Buffalo; Steve Tompson, ARL, Timothy Verstynen, Carnegie Mellon University. The study was funded under an Army Collaborative Technology Alliance (


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