Title
Learning with the molecular-based hypernetwork model
Date Issued
01 January 2001
Access level
metadata only access
Resource Type
conference paper
Author(s)
Conrad M.
Wayne State University
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
The hypernetwork model is a hierarchical architecture that has a representation of the molecular, cellular, and organismic levels of biological organization. Influences flow within each level, and through levels, forming dynamic networks of molecular interactions. With its molecular variation-selection learning algorithm, the hypernetwork is able to solve fairly complex tasks such as the (4-10)-input parity task, and the tic-tac-toe endgame problem, with good results. These performance illustrates the learning capabilities of this model.
Start page
1177
End page
1182
Volume
2
Language
English
OCDE Knowledge area
Ciencias de la computación
Subjects
Scopus EID
2-s2.0-0034863650
Source
Proceedings of the IEEE Conference on Evolutionary Computation, ICEC
Resource of which it is part
Proceedings of the IEEE Conference on Evolutionary Computation, ICEC
Conference
Congress on Evolutionary Computation 2001
Sources of information:
Directorio de Producción Científica
Scopus