A Cognitive Model of Concept Learning with a Flexible Internal Representation System

Authors:
Toshihiko Matsuka;Yasuaki Sakamoto
Affiliations:
Center for Decision Technologies, Wesley J. Howe School of Technology Management, Stevens Institute of Technology, Hoboken, NJ 07030, USA;Center for Decision Technologies, Wesley J. Howe School of Technology Management, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

In the human mind, high-order knowledge is categorically organized, yet the nature of its internal representation system is not well understood. While it has been traditionally considered that there is a single innate representation system in our mind, recent studies suggest that the representational system is a dynamic, capable of adjusting a representation scheme to meet situational characteristics. In the present paper, we introduce a new cognitive modeling framework accounting for the flexibility in representing high-order category knowledge. Our modeling framework flexibly learns to adjust its internal knowledge representation scheme using a meta-heuristic optimization method. It also accounts for the multi-objective and the multi-notion natures of human learning, both of which are indicated as very important but often overlooked characteristics of human cognition.