Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
A Self-Organizing Model of Hyperinformation
Akira NAMATAME
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1993 Volume 6 Issue 7 Pages 319-327

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Abstract

I propose a self-organizing model of hierarchical information. The hierarchical representation and learning algorithm are designed for the high-level information processing using neural networks. In this paper, I deal with both learning acqusition and representation issues in a single framework. The whole complex knowledge structure can be acquired through the piecewise relational information among hierarchical information. The self-organizing hierarchical information is implemented from an object-oriented programming paradigm, Inferences are proceeded by sending and receiving messages among information-objects. Since they are proceeded inside information objects, the inference processes are autonomous and parallel.

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