Evolving neural induction regular language using combined evolutionary algorithms

Jinn-Moon Yang*, Cheng Yan Kao, Jorng Tzong Horng

*Corresponding author for this work

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

7 Scopus citations

Abstract

This paper proposes a new algorithm called combined evolutionary algorithm (CEA) to train a neural network, and demonstrates its use in inducing thefinite state automata task. This algorithm evolves neural networks by incorporating the ideas of evolutionary programming(EP) and real coded genetic algorithms (RCGA) into evolution strategies (ESs). Simultaneously, we add the local competition into the CEA in order to reduce the complexity and maintain the diversity. This algorithm is able to balance the exploration and exploitation dynamically. We implement CEA and experiment on seven benchmark problems of regular language. The results indicate that the CF-4 is a powerful technique to construct neural networks.

Original languageEnglish
Title of host publicationProceedings ISAI / IFIS 1996 Mexico - USA Collaboration in Intelligent Systems Technologies
EditorsRogelio Soto, Jose M. Sanchez, Francisco J. Cantu-Ortiz, Moraima Campbell
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages162-169
Number of pages8
ISBN (Electronic)9682994373, 9789682994371
StatePublished - 1 Dec 1996
EventProceedings of the 1996 1st Joint Conference on Intelligent Systems/ISAI/IFIS - Cancun, Mex
Duration: 12 Nov 199615 Nov 1996

Publication series

NameProceedings ISAI / IFIS 1996 Mexico - USA Collaboration in Intelligent Systems Technologies

Conference

ConferenceProceedings of the 1996 1st Joint Conference on Intelligent Systems/ISAI/IFIS
CityCancun, Mex
Period12/11/9615/11/96

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