The US Defence Advanced Research Projects Agency is seeking to automate air-to-air combat, enabling reaction times at machine speeds and freeing pilots to concentrate on the larger air battle.
No ArtificiaI Intelligence (AI) currently exists that can outduel a human pilot in a fighter jet in a high-speed, high-G dogfight, a DARPA release said. Turning aerial dogfighting over to AI is about giving pilots the confidence that AI and automation can handle a high-end fight.
A new DARPA project aims to accelerate the transformation of pilots from aircraft operators to mission battle commanders who can entrust dynamic air combat tasks to unmanned, semi-autonomous airborne assets from the cockpit.
To pursue this vision, DARPA created the Air Combat Evolution (ACE) program to use human-machine collaborative dogfighting as its initial challenge scenario. DARPA will hold a Proposers Day for interested researchers on May 17, 2019, in Arlington, Virginia.
“Being able to trust autonomy is critical as we move toward a future of warfare involving manned platforms fighting alongside unmanned systems,” said Air Force Lt. Col. Dan Javorsek (Ph.D.), ACE program manager in DARPA’s Strategic Technology Office (STO). “We envision a future in which AI handles the split-second maneuvering during within-visual-range dogfights, keeping pilots safer and more effective as they orchestrate large numbers of unmanned systems into a web of overwhelming combat effects.”
ACE is one of several STO programs designed to enable DARPA’s “mosaic warfare” vision. Mosaic warfare shifts warfighting concepts away from a primary emphasis on highly capable manned systems, with their high costs and lengthy development timelines, to a mix of manned and less-expensive unmanned systems that can be rapidly developed, fielded, and upgraded with the latest technology to address changing threats.
Linking together manned aircraft with significantly cheaper unmanned systems creates a “mosaic” where the individual “pieces” can easily be recomposed to create different effects or quickly replaced if destroyed, resulting in a more resilient warfighting capability.
The ACE program will train AI in the rules of aerial dogfighting similar to how new fighter pilots are taught, starting with basic fighter maneuvers in simple, one-on-one scenarios. While highly nonlinear in behavior, dogfights have a clearly defined objective, measureable outcome, and the inherent physical limitations of aircraft dynamics, making them a good test case for advanced tactical automation.
Like human pilot combat training, the AI performance expansion will be closely monitored by fighter instructor pilots in the autonomous aircraft, which will help co-evolve tactics with the technology. These subject matter experts will play a key role throughout the program.
Javorsek said, “following virtual testing, we plan to demonstrate the dogfighting algorithms on sub-scale aircraft leading ultimately to live, full-scale manned-unmanned team dogfighting with operationally representative aircraft.”
Before Phase 1 of the program begins, DARPA will sponsor a stand-alone, limited-scope effort focused on automating individual tactical behavior for one-on-one dogfights. Called the “AlphaDogfight Trials,” to will pit AI dogfighting algorithms against each other in a tournament-style competition.“We intend to tap the top algorithm developers in the air combat simulation and gaming communities,” Javorsek said.
The United States Defense Advanced Research Projects Agency is currently working on 20 different artificial intelligence (AI) programs. First announced in September, the DARPA AI Next campaign is a multi-year, upwards of $2 billion investment in new and existing programs to create the third wave of AI technologies
The US Defence Advanced Research Projects Agency (DARPA) has announced a more than $2 Billion investment into “AI Next”, the future wave of artificial intelligence technologies to create collaborative partnerships between humans and machines. Under AI Next, key areas to be explored may include automating critical DoD business processes, such as security clearance vetting in a week or accrediting software systems in one day for operational deployment; improving the robustness and reliability of AI systems; enhancing the security and resiliency of machine learning and AI technologies; reducing power, data, and performance inefficiencies; and pioneering the next generation of AI algorithms and...
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