![[Artist's Concept] Army researchers develop a reinforcement learning approach called Hierarchical Reinforcement Learning that will allow swarms of unmanned aerial and ground vehicles to optimally accomplish various missions while minimizing performance uncertainty on the battlefield (Shutterstock).](https://dsiac.org/wp-content/uploads/bb-plugin/cache/size0-9-panorama-5722164280e7cbe9bcdee3a26067d73e-606cdedb7e0c3.jpg "size0 (9)")
ADELPHI, Md. — Army researchers developed a reinforcement learning approach that will allow swarms of unmanned aerial and ground vehicles to optimally accomplish various missions while minimizing performance uncertainty.
Swarming is a method of operations where multiple autonomous systems act as a cohesive unit by actively coordinating their actions.
Army researchers said future multidomain battles will require swarms of dynamically-coupled, coordinated heterogeneous mobile platforms to overmatch enemy capabilities and threats targeting U.S. forces.