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Evolutionary algorithms (EA) reproduce essential elements of the biological evolution in a computer algorithm in order to solve “difficult” problems, at least approximately, for which no exact or satisfactory solution methods are known.
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 .
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 ...
An evolutionary algorithm (EA) is a heuristic optimization algorithm using techniques inspired by mechanisms from organic evolution such as mutation, recombination, and natural selection to find an optimal configuration for a specific system within specific constraints.
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.
Michalski, R. S. (2000), "LEARNABLE EVOLUTION MODEL Evolutionary Processes Guided by Machine Learning", Machine Learning, 38: 9–40, doi: 10.1023/A:1007677805582 Michalski, R .S. (June 11–13, 1998), "Learnable Evolution: Combining Symbolic and Evolutionary Learning", Proceedings of the Fourth International Workshop on Multistrategy Learning ...
Evolution strategy (ES) from computer science is a subclass of evolutionary algorithms, which serves as an optimization technique. [1] It uses the major genetic operators mutation , recombination and selection of parents .
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.