The ALPHA artificial intelligence (AI) created by a University of Cincinnati doctoral graduate is a milestone in the use of genetic-fuzzy systems with specific implementation in unmanned combat aerial vehicles (UCAVs) in simulated air-combat missions. ALPHA's programming involved deconstructing the challenges of aerial fighter deployment into sub-decisions consisting of high-level tactics, firing, evasion, and defensiveness. The language-based fuzzy-logic algorithms cover a multitude of variables, and ease the instilling of expert knowledge into the AI; ALPHA's programming also can be generationally improved.
The earliest version of ALPHA consistently beat other AI opponents used by the U.S. Air Force Research Laboratory for research purposes. Subsequent matches against a more mature iteration by a human opponent also proved the AI's invincibility, as retired U.S. Air Force Colonel Gene Lee could not defeat ALPHA, and was consistently bested by the program during protracted clashes in a flight simulator. ALPHA also has repeatedly beaten other experts, even in conditions when the UCAVs it controls are deliberately impaired.
ALPHA is so fast it could consider and coordinate the optimal tactical plan and precise responses within a dynamic setting more than 250 times faster than human adversaries can blink. Experts say this breakthrough furthers the probability that AI-controlled UCAVs will serve as wingmen for manned aircraft on combat missions.
From UC Magazine
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