Genetic Fuzzy Tree AI Beats Tactical Experts in Combat Simulations

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October 24, 2016 | Originally published by Date Line: October 24 on

UC ALPHA AI recently won out during simulated aerial combat against U.S. expert tacticians.  It did so using no more than the processing power available in a tiny, affordable computer (Raspberry Pi) that retails for as little as $35.

Artificial intelligence (AI) developed by a University of Cincinnati doctoral graduate was recently assessed by subject-matter expert and retired United States Air Force Colonel Gene Lee — who holds extensive aerial combat experience as an instructor and Air Battle Manager with considerable fighter aircraft expertise — in a high-fidelity air combat simulator.

The artificial intelligence, dubbed ALPHA, was the victor in that simulated scenario, and according to Lee, is “the most aggressive, responsive, dynamic and credible AI I’ve seen to date.”

Details on ALPHA – a significant breakthrough in the application of what’s called genetic-fuzzy systems are published in the most-recent issue of the Journal of Defense Management, as this application is specifically designed for use with Unmanned Combat Aerial Vehicles (UCAVs) in simulated air-combat missions for research purposes.

The tools used to create ALPHA as well as the ALPHA project have been developed by Psibernetix, Inc., recently founded by UC College of Engineering and Applied Science 2015 doctoral graduate Nick Ernest, now president and CEO of the firm; as well as David Carroll, programming lead, Psibernetix, Inc.; with supporting technologies and research from Gene Lee; Kelly Cohen, UC aerospace professor; Tim Arnett, UC aerospace doctoral student; and Air Force Research Laboratory sponsors.