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  2. Evolutionary algorithm - Wikipedia

    en.wikipedia.org/wiki/Evolutionary_algorithm

    Evolutionary algorithms often perform well approximating solutions to all types of problems because they ideally do not make any assumption about the underlying fitness landscape. Techniques from evolutionary algorithms applied to the modeling of biological evolution are generally limited to explorations of microevolutionary processes and ...

  3. Evolutionary computation - Wikipedia

    en.wikipedia.org/wiki/Evolutionary_computation

    Evolutionary computation from computer science is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms.

  4. Evolutionary programming - Wikipedia

    en.wikipedia.org/wiki/Evolutionary_programming

    Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover. [ 1 ] [ 2 ] Evolutionary programming differs from evolution strategy ES( μ + λ {\displaystyle \mu +\lambda } ) in one detail. [ 1 ]

  5. 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.

  6. Genetic algorithm - Wikipedia

    en.wikipedia.org/wiki/Genetic_algorithm

    Evolutionary algorithms is a sub-field of evolutionary computing. Evolution strategies (ES, see Rechenberg, 1994) evolve individuals by means of mutation and intermediate or discrete recombination. ES algorithms are designed particularly to solve problems in the real-value domain. [58] They use self-adaptation to adjust control parameters of ...

  7. Neuroevolution - Wikipedia

    en.wikipedia.org/wiki/Neuroevolution

    Neuroevolution, or neuro-evolution, is a form of artificial intelligence that uses evolutionary algorithms to generate artificial neural networks (ANN), parameters, and rules. [1] It is most commonly applied in artificial life, general game playing [2] and evolutionary robotics.

  8. DEAP (software) - Wikipedia

    en.wikipedia.org/wiki/DEAP_(software)

    Distributed Evolutionary Algorithms in Python (DEAP) is an evolutionary computation framework for rapid prototyping and testing of ideas. [2] [3] [4] It incorporates the data structures and tools required to implement most common evolutionary computation techniques such as genetic algorithm, genetic programming, evolution strategies, particle swarm optimization, differential evolution, traffic ...

  9. Category:Applications of evolutionary algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Applications_of...

    Download as PDF; Printable version; In other projects Appearance. move to sidebar hide. Help. Applications of evolutionary algorithms Pages in category "Applications ...