IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning
Chapter
Accepted version
Åpne
Permanent lenke
http://hdl.handle.net/11250/2627222Utgivelsesdato
2019Metadata
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Originalversjon
10.1145/3365871.3365911Sammendrag
We describe IoT Sensor Gym, a framework to train the behavior of constrained IoT devices using deep reinforcement learning. We focus on the main architectural choices to align problems from the IoT domain with cutting-edge reinforcement learning algorithms and exemplify our results with the autonomous control of a solar-powered IoT device.