Uniform crossover in genetic algorithms
Proceedings of the third international conference on Genetic algorithms
Biases in the crossover landscape
Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Learning gene linkage to efficiently solve problems of bounded difficulty using genetic algorithms
Learning gene linkage to efficiently solve problems of bounded difficulty using genetic algorithms
Emergence: from chaos to order
Emergence: from chaos to order
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
The Proportional Genetic Algorithm: Gene Expression in a Genetic Algorithm
Genetic Programming and Evolvable Machines
Learning Sequential Decision Rules Using Simulation Models and Competition
Machine Learning - Special issue on genetic algorithms
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Self-Assembly of DNA-like Structures In Silico
Genetic Programming and Evolvable Machines
The behavior of adaptive systems which employ genetic and correlation algorithms
The behavior of adaptive systems which employ genetic and correlation algorithms
Nonlinearities in genetic adaptive search.
Nonlinearities in genetic adaptive search.
Genetic Programming IV: Routine Human-Competitive Machine Intelligence
Genetic Programming IV: Routine Human-Competitive Machine Intelligence
Genetic Programming and Evolvable Machines
The proteomics approach to evolutionary computation: an analysis of proteome-based location independent representations based on the proportional genetic algorithm
A comparison of the fixed and floating building block representation in the genetic algorithm
Evolutionary Computation
Ptgas---genetic algorithms evolving noncoding segments by means of promoter/terminator sequences
Evolutionary Computation
Putting more genetics into genetic algorithms
Evolutionary Computation
Intelligent automated control of life support systems using proportional representations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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A key property for predicting the effectiveness of stochastic search techniques, including evolutionary algorithms, is the existence of a positive correlation between the form and the quality of candidate solutions. In this paper we show that when the ordering of genomic symbols in a genetic algorithm is completely independent of the fitness function and therefore free to evolve along with the candidate solutions it encodes, the resulting genomes self-organize into self-similar structures that favor this key stochastic search property.