Learning predictive representations

  title={Learning predictive representations},
  author={J. Michael Herrmann and Klaus Pawelzik and Theo Geisel},
We demonstrate by a schematic model of an unexperienced animal exploring an environment that it is possible to evolve structures for perception, representation and action simultaneously from a single criterion, namely the error in predicting future sensory inputs. In order to organize successful representations of the environment actions are chosen which are expected to maximize the increase of knowledge. Initially trivial behaviors are generated that allow to learn to recognize places, whereas… CONTINUE READING
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Bu K ltho ! , Learning view graphs for robot navigation , Autonom

  • B. Scho K lkopf, H. A. Mallot, H. H.
  • 1998

BuK ltho!, Learning view graphs for robot navigation

  • M. O. Franz, B. SchoK lkopf, H.H.H.A. Mallot
  • Autonom. Robots
  • 1998

Knowing your place in the real world, ECAL-97

  • T. Duckett, U. Nehmzow
  • Fourth European Conference on Arti"cial Life…
  • 1997

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