The DARPA AlphaDogfight Trials aim to demonstrate the feasibility of developing effective, intelligent autonomous agents capable of defeating adversary aircraft in a dogfight.
AlphaDogfight Trials Competition #3 is being broadcast live from the Johns Hopkins University Applied Physics Lab (JHU/APL) via a ZoomGov Webinar on 18-20 August 2020.
DARPA’s AlphaDogfight Trials seeks to advance the state of artificial intelligence (AI) technologies applied to air combat operations. The trials are a computer-based competition designed to demonstrate advanced AI algorithms that can perform simulated within-visual-range air combat maneuvering, otherwise known as a dogfight. The goal is to use the dogfight as the challenge problem to increase performance and trust in AI algorithms and bring together the AI research and operator communities.
In August 2019, DARPA selected eight technically and organizationally diverse teams to compete in the AlphaDogfight Trials with the purpose to energize and expand a base of researchers and developers applying AI technologies to complex operational problems.
The first of three AlphaDogfight Trials competition events was held at JHU/APL in November 2019. Trial #1 was an exhibition match with the opportunity for teams to compete against different APL developed adversary agents and test the simulation environment at scale.
Trial #2 held in January 2020, was the first competition where teams were ranked against each other and tested their agents against more challenging adversary agents.
Trial #3 is the final competition. Teams will compete against each other in a bracket style competition with the top team advancing to fight against a USAF fighter pilot in a simulated dogfight.
AlphaDogfight Trials is a precursor to the DARPA Air Combat Evolution (ACE) program, which involves AI development and demonstration in three program phases – modeling and simulation, sub-scale aircraft, and full-scale aircraft testing. Ultimately, ACE will be flying AI algorithms on live aircraft to demonstrate trusted, scalable, human-level autonomy for air combat.