Learning Fine Motion by Using theHierarchical Extended
نویسنده
چکیده
A Hierarchical Extended Kohonen Map (HEKM) learns to associate actions to perceptions under the supervision of a planner: they cooperate to solve path nding problems. We argue for the utility of using the hierarchical version of the KM instead of the \\at" KM. We measure the beneets of cooperative learning due to the interaction of neighboring neurons in the HEKM. We highlight a beneecial side-eeect obtained by transferring motion skill from the planner to the HEKM, namely, smoothness of motion.
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