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U.S. Army researchers have developed a reinforcement learning approach that will allow swarms of unmanned aerial and ground vehicles more consistent performance when executing mission objectives.
Reinforcement learning provides a way to control uncertain agents to achieve multi-objective goals when the precise model for the agent is unavailable. However, existing reinforcement learning methods can only be applied in a centralized manner, which requires pooling the state information of the entire swarm at a central learner, which drastically increases computational complexity and communication requirements, resulting in unreasonable learning time, Jermin George of the U.S. Army Combat Capabilities Development Command’s Army…READ MORE