SensorDrop: A Reinforcement Learning Framework for Communication Overhead Reduction on the Edge

no code implementations • 3 Oct 2019 • Pooya Khandel, Amir Hossein Rassafi, Vahid Pourahmadi, Saeed Sharifian, Rong Zheng

As such decisions are application dependent and may change over time, they should be learned during the operation of the system, for that we propose a method based on Advantage Actor-Critic (A2C) reinforcement learning which gradually learns which sensor's data is cost-effective to be sent to the central node.

reinforcement-learning Reinforcement Learning (RL)