Discovery and sharing of knowledge with self-organized agents

Author

Wickramasinghe, L.K. ; Alahakoon, L.D.

Author_Institution

Sch. of Bus. Syst., Monash Univ., Australia

fYear

2003

fDate

13-16 Oct. 2003

Firstpage

126

Lastpage

132

Abstract

This paper describes a system, which has the capability to analyze and discover knowledge gathered from distributed sources. This autonomous system is implemented using the growing self organizing map (GSOM), which is a dynamic version of the self organizing map (SOM) and a multi agent communication system. The important contribution of this model is its ability to transfer local knowledge to a central knowledge base referred to as a central controller where the data is clustered and analyzed to identify similarities and variations. The central controller has the capability of transferring back its global knowledge to the distributed sources.

Keywords

data mining; multi-agent systems; self-organising feature maps; autonomous system; central controller; central knowledge base; clustered data; data mining; distributed agents; distributed sources; global knowledge; growing self organizing map; hierarchical clustering; knowledge discovery; knowledge sharing; local knowledge transfer; multi agent communication; multiagent system; self-organized agents; unsupervised learning; Centralized control; Communication system control; Data analysis; Data mining; Data structures; Flexible structures; Neural networks; Self organizing feature maps; Skeleton; Unsupervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Agent Technology, 2003. IAT 2003. IEEE/WIC International Conference on

Print_ISBN

0-7695-1931-8

Type

conf

DOI

10.1109/IAT.2003.1241058

Filename

1241058