Artificial intelligence recently won out during simulated aerial combat against U.S. expert tacticians. Importantly, 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.
Not only was Lee not able to score a kill against ALPHA after repeated attempts, he was shot out of the air every time during protracted engagements in the simulator
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.
High pressure and fast pace: An artificial intelligence sparring partner
ALPHA is currently viewed as a research tool for manned and unmanned teaming in a simulation environment. In its earliest iterations, ALPHA consistently outperformed a baseline computer program previously used by the Air Force Research Lab for research. In other words, it defeated other AI opponents.
In fact, it was only after early iterations of ALPHA bested other computer program opponents that Lee then took to manual controls against a more mature version of ALPHA last October. Not only was Lee not able to score a kill against ALPHA after repeated attempts, he was shot out of the air every time during protracted engagements in the simulator.
Since that first human vs. ALPHA encounter in the simulator, this AI has repeatedly bested other experts as well, and is even able to win out against these human experts when its (the ALPHA-controlled) aircraft are deliberately handicapped in terms of speed, turning, missile capability and sensors.
Lee, who has been flying in simulators against AI opponents since the early 1980s, said of that first encounter against ALPHA, “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.”
He added that with most AIs, “an experienced pilot can beat up on it (the AI) if you know what you’re doing. Sure, you might have gotten shot down once in a while by an AI program when you, as a pilot, were trying something new, but, until now, an AI opponent simply could not keep up with anything like the real pressure and pace of combat-like scenarios.”
But, now, it’s been Lee, who has trained with thousands of U.S. Air Force pilots, flown in several fighter aircraft and graduated from the U.S. Fighter Weapons School (the equivalent of earning an advanced degree in air combat tactics and strategy), as well as other pilots who have been feeling pressured by ALPHA.
And, anymore, when Lee flies against ALPHA in hours-long sessions that mimic real missions, “I go home feeling washed out. I’m tired, drained and mentally exhausted. This may be artificial intelligence, but it represents a real challenge.”
An artificial intelligence wingman: How an AI combat role might develop
Explained Ernest, “ALPHA is already a deadly opponent to face in these simulated environments. The goal is to continue developing ALPHA, to push and extend its capabilities, and perform additional testing against other trained pilots. Fidelity also needs to be increased, which will come in the form of even more realistic aerodynamic and sensor models. ALPHA is fully able to accommodate these additions, and we at Psibernetix look forward to continuing development.”
In the long term, teaming artificial intelligence with U.S. air capabilities will represent a revolutionary leap. Air combat as it is performed today by human pilots is a highly dynamic application of aerospace physics, skill, art, and intuition to maneuver a fighter aircraft and missiles against adversaries, all moving at very high speeds. After all, today’s fighters close in on each other at speeds in excess of 1,500 miles per hour while flying at altitudes above 40,000 feet. Microseconds matter, and the cost for a mistake is very high.
Eventually, ALPHA aims to lessen the likelihood of mistakes since its operations already occur significantly faster than do those of other language-based consumer product programming. In fact, ALPHA can take in the entirety of sensor data, organize it, create a complete mapping of a combat scenario and make or change combat decisions for a flight of four fighter aircraft in less than a millisecond. Basically, the AI is so fast that it could consider and coordinate the best tactical plan and precise responses, within a dynamic environment, over 250 times faster than ALPHA’s human opponents could blink.
So it’s likely that future air combat, requiring reaction times that surpass human capabilities, will integrate AI wingmen – Unmanned Combat Aerial Vehicles (UCAVs) – capable of performing air combat and teamed with manned aircraft wherein an onboard battle management system would be able to process situational awareness, determine reactions, select tactics, manage weapons use and more. So, AI like ALPHA could simultaneously evade dozens of hostile missiles, take accurate shots at multiple targets, coordinate actions of squad mates, and record and learn from observations of enemy tactics and capabilities.
UC’s Cohen added, “ALPHA would be an extremely easy AI to cooperate with and have as a teammate. ALPHA could continuously determine the optimal ways to perform tasks commanded by its manned wingman, as well as provide tactical and situational advice to the rest of its flight.”
The Latest on: Genetic-fuzzy systems
via Google News
The Latest on: Genetic-fuzzy systems
- AI that can shoot down fighter planes helps treat bipolar disorder on June 12, 2017 at 8:49 am
David Fleck, an associate professor at the UC College of Medicine, and his co-authors used artificial intelligence called "genetic fuzzy trees" to predict how bipolar patients would respond to lithium ... […]
- AI used to treat bipolar disorder in an app that could revolutionize medicine on June 11, 2017 at 1:01 pm
His team developed a genetic fuzzy logic called Alpha capable of shooting down human pilots in simulations, even when the computer’s aircraft intentionally was handicapped with a slower top speed and ... […]
- Researchers teach drones to land themselves on moving targets on February 23, 2017 at 8:53 am
“We want to translate this kind of fuzzy reasoning used in humans to control systems.” Fuzzy logic helps the drone make good navigational decisions amid a sea of statistical noise, he said. It’s calle... […]
- AI bests Air Force combat tactics experts in simulated dogfights on June 29, 2016 at 10:19 pm
Described in a paper recently published in the Journal of Defense Management, ALPHA was created using a "genetic fuzzy tree" (GFT) system. There's a lot to unpack in that term, but in short, the metho... […]
- An Artificial Intelligence Just Beat A Real Human In A Dogfight on June 29, 2016 at 9:32 am
But only in a simulator, for now. As Psibernetix founder Nick Ernest explained to Popular Science: “The secret to ALPHA’s superhuman flying skills is a decision-making system called a genetic fuzzy tr... […]
- Veteran Pilot Loses Simulated Dogfight to Impressive Artificial Intelligence on June 28, 2016 at 3:50 pm
ALPHA uses what are called “fuzzy logic algorithms” to form a “Genetic Fuzzy Tree” system that breaks big problems down into smaller chunks so the system can evaluate which variables are relevant to a ... […]
- AI system beats experts in aerial combat simulation on June 28, 2016 at 11:45 am
ALPHA is a significant breakthrough in the application of what is called genetic-fuzzy systems, researchers said. The application is specifically designed for use with Unmanned Combat Aerial Vehicles ... […]
- An AI Just Defeated Human Fighter Pilots in An Air Combat Simulator on June 27, 2016 at 4:59 pm
It moved instantly between defensive and offensive actions as needed,” Lee said. ALPHA makes decisions using a genetic fuzzy tree system, which is a subtype of fuzzy logic algorithms. It can calculate ... […]
- Fighter pilot AI proves unbeatable in aerial combat after besting US Air Force Colonel on June 27, 2016 at 4:59 pm
The Air Force is currently looking at how genetic fuzzy systems like ALPHA can be used in unmanned combat aerial vehicles (UCAVs) for simulated air-combat missions – although for now, they only intend ... […]
- Skynet Soars As AI Bot Destroys Top Gun Pilots In Dogfight Simulations With Raspberry Pi Level Horsepower on June 27, 2016 at 4:59 pm
ALPHA is a thoroughly modern genetic-fuzzy system. It uses Genetic Fuzzy Tree methodology (you can read up these systems with this supplemental text). What’s most impressive is that ALPHA had no troub... […]
via Bing News