TrueStory: New artificial intelligence beats tactical experts in combat simulation #AI #military #automation

Simulator at Wright Patt Air Force Base.
That AI is on my tail again. How did it get there?

Lending ever more credence to all the stories with military robots, real world AI can now outperform experienced humans in plane to plane battles.

It uses a Genetic linguistic-fuzzy tree algorithm. Tree breaks down inputs into sub-problems, linguistic-fuzzy allows for ranges of inputs defined in a language,  and the genetic part means that many randomly generated instances compete against each other, then the best ones breed to make the next generation and so on.

exerpts from the article:

“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.”

“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.”

“ALPHA and its algorithms require no more than the computing power available in a low-budget PC in order to run in real time and quickly react and respond to uncertainty and random events or scenarios.”

“the programming involved breaking up the complex challenges and problems represented in aerial fighter deployment into many sub-decisions, thereby significantly reducing the required “space” or burden for good solutions. The branches or sub divisions of this decision-making tree consists of high-level tactics, firing, evasion and defensiveness.”

“The AI algorithms that Ernest and his team ultimately developed are language based, with if/then scenarios and rules able to encompass hundreds to thousands of variables. This language-based control or fuzzy logic, while much less about complex mathematics, can be verified and validated.”

“To reach its current performance level, ALPHA’s training has occurred on a $500 consumer-grade PC. This training process started with numerous and random versions of ALPHA. These automatically generated versions of ALPHA proved themselves against a manually tuned version of ALPHA. The successful strings of code are then “bred” with each other, favoring the stronger, or highest performance versions. In other words, only the best-performing code is used in subsequent generations. Eventually, one version of ALPHA rises to the top in terms of performance, and that’s the one that is utilized.”

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