Scienceblogtwo

Individual agents, such as robots or drones, can cooperate and finish a task when communication channels are open. What happens, though, if their technology is insufficient or the signals are jammed, making communication impossible? Researchers from the University of Illinois at Urbana-Champaign began with this more challenging task. They created a technique using multi-agent reinforcement learning, a form of artificial intelligence, to teach many agents to cooperate. Huy Tran, an aeronautical engineer at Illinois, noted that it is simpler when agents can communicate with one another. "But we wanted to achieve this in a decentralized manner, so that they don't communicate with one another. We also concentrated on circumstances in which it is unclear what the various duties or responsibilities of the agents should be." Because it's unclear what one agent should do in contrast to another agent, Tran claimed that this scenario is far more complicated and a harder difficu...