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  2. Genetic algorithm - Wikipedia

    en.wikipedia.org/wiki/Genetic_algorithm

    Genetic programming often uses tree-based internal data structures to represent the computer programs for adaptation instead of the list structures typical of genetic algorithms. There are many variants of Genetic Programming, including Cartesian genetic programming , Gene expression programming , [ 62 ] grammatical evolution , Linear genetic ...

  3. Neuroevolution of augmenting topologies - Wikipedia

    en.wikipedia.org/wiki/Neuroevolution_of...

    The competing conventions problem arises when there is more than one way of representing information in a phenotype. For example, if a genome contains neurons A, B and C and is represented by [A B C], if this genome is crossed with an identical genome (in terms of functionality) but ordered [C B A] crossover will yield children that are missing information ([A B A] or [C B C]), in fact 1/3 of ...

  4. Genetic programming - Wikipedia

    en.wikipedia.org/wiki/Genetic_programming

    Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population of programs. It applies the genetic operators selection according to a predefined fitness measure , mutation and crossover .

  5. Grammatical evolution - Wikipedia

    en.wikipedia.org/wiki/Grammatical_evolution

    Grammatical evolution (GE) is a genetic programming (GP) technique (or approach) from evolutionary computation pioneered by Conor Ryan, JJ Collins and Michael O'Neill in 1998 [1] at the BDS Group in the University of Limerick.

  6. Evolutionary computation - Wikipedia

    en.wikipedia.org/wiki/Evolutionary_computation

    Three branches emerged in different places to attain this goal: evolution strategies, evolutionary programming, and genetic algorithms. A fourth branch, genetic programming, eventually emerged in the early 1990s. These approaches differ in the method of selection, the permitted mutations, and the representation of genetic data.

  7. What a $2 million per dose gene therapy reveals about drug ...

    www.aol.com/news/2-million-per-dose-gene...

    Manning, the startup’s first big investor, made more than $315 million, multiplying his original investment by about 60. (Manning didn’t respond to calls or emailed questions from ProPublica.)

  8. Crossover (evolutionary algorithm) - Wikipedia

    en.wikipedia.org/wiki/Crossover_(evolutionary...

    Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information of two parents to generate new offspring. It is one way to stochastically generate new solutions from an existing population, and is analogous to the crossover that happens during sexual ...

  9. Chromosome (evolutionary algorithm) - Wikipedia

    en.wikipedia.org/wiki/Chromosome_(evolutionary...

    Tree representations in a chromosome are used by genetic programming, an EA type for generating computer programs or circuits. [10] The trees correspond to the syntax trees generated by a compiler as internal representation when translating a computer program. The adjacent figure shows the syntax tree of a mathematical expression as an example.