An Accelerated Genetic Algorithm

Authors:
John R. Podlena;Tim Hendtlass
Affiliations:
Centre for Intelligent Systems, School of Biophysical Sciences and Electrical Engineering, Swinburne University of Technology, P.O. Box 218, Hawthorne 3122, Australia;Centre for Intelligent Systems, School of Biophysical Sciences and Electrical Engineering, Swinburne University of Technology, P.O. Box 218, Hawthorne 3122, Australia
Venue:
Applied Intelligence
Year:
1998

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Abstract

The standard Genetic Algorithm, originallyinspired by natural evolution, has displayed itseffectiveness in solving a wide variety of complexproblems. This paper describes the use of the naturalphenomenon known as the {\it Baldwin\ effect} (orcross-generational learning) as an enhancement to thestandard Genetic Algorithm. This is implemented by usingan artificial neural network to store aspects of thepopulation‘s history. It also describes a method by whichthe negative side effects of a large elite sub-populationcan be counter-balanced by using an ageing coefficient inthe fitness calculation.