Artificial intelligence development firm Psibernetix, alongside researchers from the University of Cincinnati (UC) and the US Air Force Research Laboratory (AFRL), have developed an AI for piloting unmanned arial vehicles (UAVs) they say is doing for drone flight what IBM's Deep Blue did for chess.
Dubbed ALPHA, the AI system has already bested expert pilots in air combat simulations, even when it is outnumbered and given handicaps like shorter-range missiles and a reduced payload.
According to research detailed in the Journal of Defense Management , even at its current stage ALPHA is managing over 150 variables during a combat simulation, things like the position, velocity, and acceleration of all the air craft in the field, missile range data, visibility, and the number of shots taken by opponents. In the simulation ALPHA controlled a team of UAVs (the red team) against a “blue team” of human-controlled fighters. In each scenario ALPHA is given only limited knowledge of the opposing force (it doesn't even know the number of enemies it will face) and must rely on “organic sensors and situational awareness of the blue force,” according to the study. This sort of approach is necessary to take ALPHA beyond being just a difficult video game. The challenge for a system like ALPHA is it has to be able to respond when humans try to exploit it -- when they act like Maverick from Top Gun and try to do something crazy and unpredictable to beat the computer.
UC grad and Psibernetix President and CEO Nick Ernest (left) along with David Carroll of Psibernetix (right) watch as retired Air Force Colonel Gene Lee (seated) competes against ALPHA in a combat simulation.
(Source: University of Cincinnati )
In an interview with UC, Retired US Air Force Colonel Gene Lee, who has been combating AIs in flight simulators since the 1980s, called ALPHA “the most aggressive, responsive, dynamic, and credible AI I’ve seen to date.” Lee, who was bested by ALPHA in repeated attempts, told the university,“I was surprised at how aware and reactive it was. It seemed to be aware of my intentions and reacting instantly to my changes in flight and my missile deployment. It knew how to defeat the shot I was taking. It moved instantly between defensive and offensive actions as needed.”
Perhaps what should worry pilots like Lee even more is that ALPHA is able to accomplish these tasks, something that one would expect would take a super computer, using only the processing power of a consumer-grade PC. While the version of ALPHA used in the study ran on a $500 PC, UC said the AI can operate on a platform as simple as a $35 Raspberry Pi.
How is ALPHA able to accomplish this and do so with such a low computing cost? The answer lies in a methodology developed by the researchers known as Genetic Fuzzy Tree (GFT) logic that the researchers said, “... has shown an incredible ability to obtain unparalleled levels of performance in very large and complex problems that contain all of the difficulties that alternative intelligent