Reinforcement Learning on Slow Features of High-Dimensional Input Streams

@inproceedings{Legenstein2010ReinforcementLO,
  title={Reinforcement Learning on Slow Features of High-Dimensional Input Streams},
  author={Robert A. Legenstein and Niko Wilbert and Laurenz Wiskott},
  booktitle={PLoS Computational Biology},
  year={2010}
}
Humans and animals are able to learn complex behaviors based on a massive stream of sensory information from different modalities. Early animal studies have identified learning mechanisms that are based on reward and punishment such that animals tend to avoid actions that lead to punishment whereas rewarded actions are reinforced. However, most algorithms for reward-based learning are only applicable if the dimensionality of the state-space is sufficiently small or its structure is sufficiently… CONTINUE READING
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