The US Army Research Laboratory says it is experimenting with reinforcement learning algorithms to control swarms of drones and autonomous vehicles to overwhelm and dominate America's enemies.
“Finding optimal guidance policies for these swarming vehicles in real-time is a key requirement for enhancing warfighters' tactical situational awareness, allowing the US Army to dominate in a contested environment,”
said Dr Jemin George, a scientist at the US Army Combat Capabilities Development Command, a boffinry nerve center of the US Army.
Dr George and his colleagues developed a method to control large swarms of agents by collecting them into groups using hierarchical reinforcement learning (
HRL). By shifting drone control from a centralized approach to a hierarchical design, learning time for the software was cut 80 per cent, we're told.
Crucially, it means swarms of trained, unmanned equipment can be sent to particular areas with a set of instructions, and each collective maintains formation automatically among themselves to carry out those orders. Thus, human controllers won't have to worry about individual drones and vehicles, just point the groups at particular positions on a map; the machines will have learned to figure out their positioning for themselves, and as a team go where they are ordered and work together as intended, like a combat unit.
