Paper available: Learning Fine Motion by Using the Hierarchical Extended Kohonen Map

[Cristina Versino]

``Learning Fine Motion by Using the Hierarchical Extended Kohonen Map''

Cristina Versino and Luca Maria Gambardella

IDSIA, Corso Elvezia 36, 6900 Lugano, Switzerland
cristina at idsia.ch, luca at idsia.ch 

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.

In Proc. ICANN96, International Conference on Artificial Neural Networks, Bochum, Germany, 17--19 July, pp. 221--226.

You can obtain a copy (6 pages, 135K in compressed form) via:
1) netscape ftp://ftp.idsia.ch/pub/cristina/icann96.ps.gz
2) ftp 
3) visiting recent IDSIA papers page: http://www.idsia.ch/reports.html