A game-theoretic adaptive categorization mechanism for ART-type networks

Wai Keung Fung, Yun Hui Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

A game-theoretic formulation of adaptive categorization mechanism for ART-type networks is proposed in this paper. We have derived the game-theoretic model ΓAC for competitive processes of categorization of ART-type networks and an update rule for vigilance parameters using the concept of learning automata. Numbers of clusters generated by ART adaptive categorization are similar regardless of the initial vigilance parameters ρ assigned to the ART networks as demonstrated in the experiments provided. The proposed ART adaptive categorization mechanism can thus avoid the problem of choosing suitable vigilance parameter a priori for pattern categorization.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2001 - International Conference, Proceedings
EditorsKurt Hornik, Georg Dorffner, Horst Bischof
PublisherSpringer Verlag
Pages170-176
Number of pages7
ISBN (Print)3540424865, 9783540446682
DOIs
Publication statusPublished - Jan 2001
Externally publishedYes
EventInternational Conference on Artificial Neural Networks, ICANN 2001 - Vienna, Austria
Duration: 21 Aug 200125 Aug 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2130
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Artificial Neural Networks, ICANN 2001
Country/TerritoryAustria
CityVienna
Period21/08/0125/08/01

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