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Learning fine motion by using the Hierarchical Extended Kohonen Map

  • Cristina Versino
  • Luca Maria Gambardella
Oral Presentations: Applications Applications in Robotics
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1112)

Abstract

A Hierarchical Extended Kohonen Map (HEKM) learns to associate actions to perceptions under the supervision of a planner: they cooperate to solve path finding problems. We argue for the utility of using the hierarchical version of the KM instead of the “flat” KM. We measure the benefits of cooperative learning due to the interaction of neighboring neurons in the HEKM. We highlight a beneficial side-effect obtained by transferring motion skill from the planner to the HEKM, namely, smoothness of motion.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Cristina Versino
    • 1
  • Luca Maria Gambardella
    • 1
  1. 1.IDSIALuganoSwitzerland

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