Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction

Scientific reports, Volume 7, Issue 1, 2017, Pages 17562-17562.

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Abstract:

Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feed...More

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