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The Evidence for Evolution02:55

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Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
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Weighted Hierarchical Grammatical Evolution.

Alberto Bartoli, Mauro Castelli, Eric Medvet

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    Summary
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    Weighted Hierarchical Grammatical Evolution (WHGE) introduces a novel genotype-phenotype mapping for evolutionary computation. This method enhances fitness and mapping properties without constraining the Grammatical Evolution framework.

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    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Evolutionary Computation

    Background:

    • Grammatical Evolution (GE) is a widely used evolutionary computation technique.
    • GE maps bit string genotypes to phenotype strings defined by context-free grammars.
    • Existing GE methods have limitations in genotype-phenotype mapping efficiency and flexibility.

    Purpose of the Study:

    • To introduce Weighted Hierarchical Grammatical Evolution (WHGE), a novel genotype-phenotype mapping procedure for GE.
    • To enhance the efficiency and properties of the genotype-phenotype mapping in GE.
    • To evaluate WHGE against standard GE and other advanced techniques.

    Main Methods:

    • WHGE imposes a hierarchy on the genotype.
    • Grammar symbols are encoded using a variable number of bits based on their expressive power.
    • WHGE is compatible with recursive grammars and standard genetic operators, without pre-defined phenotype size bounds.

    Main Results:

    • WHGE demonstrated very good results on challenging benchmarks.
    • The proposed method achieved superior fitness compared to standard GE and other enhancements.
    • WHGE improved the properties of the genotype-phenotype mapping procedure.

    Conclusions:

    • WHGE offers a significant advancement in Grammatical Evolution.
    • The novel mapping procedure enhances both performance and mapping characteristics.
    • WHGE provides a flexible and effective approach for genotype-phenotype mapping in evolutionary computation.