A new chapter has appeared in the story of machines defeating humans: the AI once again defeated a human pilot in virtual air combat. The AlphaDogfight competition was the final test of neural network algorithms developed for the US military. And the best demonstration of the capabilities of intelligent autonomous agents capable of defeating enemy aircraft in aerial combat. More details – in the material Cloud4Y.
This isn’t the first time an AI has defeated a human pilot. Tests in 2016 showed that an artificial intelligence system can beat an experienced combat flight instructor. But Thursday’s DARPA simulation was arguably more meaningful, as it pitted many algorithms against each other and then against humans in challenging environments. In addition to integrating AI into combat vehicles to enhance their combat capability, simulations like these can also help train human pilots.
Last August, the Defense Advanced Research Project Agency (DARPA) selected eight teams to participate in a series of tests. The list includes Aurora Flight Sciences, EpiSys Science, Georgia Tech Research Institute, Heron Systems, Lockheed Martin, Perspecta Labs, PhysicsAI and SoarTech (as you can understand, along with large defense industry contractors like Lockheed Martin, small companies like Heron Systems).
The goal of the program was to create AI systems for combat drones and unmanned wingmen covering manned fighters. Scientists and the military expect that AI will be able to conduct aerial combat faster and more efficiently than a person, and reduce the burden on the pilot, giving him time to make important tactical decisions within a larger combat mission.
The first phase of the AlphaDogfight Trials was held in November 2019 at the Applied Physics Laboratory of Johns Hopkins University. On it, neural network algorithms created by different teams fought an air battle with the Red artificial intelligence system, created by DARPA specialists. The battles between the algorithms were fought in 1×1 mode at a low difficulty level. The second stage of testing took place in January 2020. It differed from the first in increased complexity. The final test stage, which took place on August 20, 2020, could be viewed live on YouTube channel DARPA…
The tests were carried out in the FlightGear aircraft simulator using the JSBSim flight dynamics software model. In the first two stages, neural network algorithms controlled the F-15C Eagle heavy fighters, and in the third, the medium F-16 Fighting Falcon.