Researchers at the MIT used a reinforcement learning approach that is decentralized, which means the agents learn to win the games independently, making the system more scalable. The framework could be used by a group of autonomous drones working together to find a lost hiker in a thick forest, or by self-driving cars that strive to keep passengers safe by anticipating future moves of other vehicles driving on a busy highway.