On location independent representations and self-organization

Authors:
Ivan Garibay;Annie S. Wu;Ozlem Garibay
Affiliations:
University of Central Florida, Suite, Orlando, FL;University of Central Florida, Orlando, FL;University of Central Florida, Orlando, FL
Venue:
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Year:
2005

Citing 2
Cited 0

The Proportional Genetic Algorithm: Gene Expression in a Genetic Algorithm

Genetic Programming and Evolvable Machines
On favoring positive correlations between form and quality of candidate solutions via the emergence of genomic self-similarity

GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation

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Abstract

We study the self-organization of genomic symbols on a genetic algorithm with a location independent representation—the Proportional Genetic Algorithm (PGA) [2]. Self-organization of genomic symbols is possible because location independent representations ensure the absence of selective pressure for a particular order. We hypothesize that self-similarity emerges because self-similar genomes are more robust with respect to crossover and mutation and because it favors positive correlations between the form and quality of candidate solutions.