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  2. 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 ...

  3. Evolutionary algorithm - Wikipedia

    en.wikipedia.org/wiki/Evolutionary_algorithm

    In computational intelligence (CI), an evolutionary algorithm (EA) is a subset of evolutionary computation, [1] a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution , such as reproduction , mutation , recombination and selection .

  4. Mutation (evolutionary algorithm) - Wikipedia

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

    The classic example of a mutation operator of a binary coded genetic algorithm (GA) involves a probability that an arbitrary bit in a genetic sequence will be flipped from its original state. A common method of implementing the mutation operator involves generating a random variable for each bit in a sequence.

  5. Gene expression programming - Wikipedia

    en.wikipedia.org/wiki/Gene_expression_programming

    Gene expression programming (GEP) in computer programming is an evolutionary algorithm that creates computer programs or models. These computer programs are complex tree structures that learn and adapt by changing their sizes, shapes, and composition, much like a living organism.

  6. Selection (evolutionary algorithm) - Wikipedia

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

    Selection is the stage of a genetic algorithm or more general evolutionary algorithm in which individual genomes are chosen from a population for later breeding (e.g., using the crossover operator). Selection mechanisms are also used to choose candidate solutions (individuals) for the next generation.

  7. Evolutionary programming - Wikipedia

    en.wikipedia.org/wiki/Evolutionary_programming

    Evolutionary programming is an evolutionary algorithm used to evolve finite-state machines as predictors. [1] It is one of the four major evolutionary algorithm paradigms. [2] It was first used by Lawrence J. Fogel in the US in 1960 in order to use simulated evolution as a learning process aiming to generate artificial intelligence. [3]

  8. Genetic algorithm - Wikipedia

    en.wikipedia.org/wiki/Genetic_algorithm

    Download as PDF; Printable version; In other projects ... Another approach was the evolutionary programming technique of ... Genetic Algorithms in Python Tutorial ...

  9. Differential evolution - Wikipedia

    en.wikipedia.org/wiki/Differential_evolution

    In evolutionary computation, differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Such methods are commonly known as metaheuristics as they make few or no assumptions about the optimized problem and can search very large spaces of ...