Deep Reinforcement Learning Using Neurophysiological Signatures of Interest

We present a study where human neurophysiological signals are used as implicit feedback to alter the behavior of a deep learning based autonomous driving agent in a simulated virtual environment.
Accepted 6 March 2017
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