Constructivist Learning: A Neural Implementation of the Schema Mechanism (2003)
Constructivist learning is a hierarchical part-to-whole learning system used by humans and desirable for use by robots. Current implementations are too resource-intensive to be used for anything but simple environments. In this paper, we reimplement one such system, the Schema Mechanism, using a hierarchy of self-organizing maps. The result is an efficient system for learning perceptual and action schemas that can be used in real-world applications like robotics.
In Proceedings of WSOM '03: Workshop for Self-Organizing Maps, Kitakyushu, Japan, 2003.

Harold H. Chaput Ph.D. Alumni hchaput [at] ea com
Benjamin Kuipers kuipers [at] cs utexas edu
Risto Miikkulainen Faculty risto [at] cs utexas edu