Evolutionary programming is one of the four major
evolutionary algorithm paradigms
In science and philosophy, a paradigm () is a distinct set of concepts or thought patterns, including theories, research methods, postulates, and standards for what constitute legitimate contributions to a field.
Etymology
''Paradigm'' comes f ...
. It is similar to
genetic programming, but the structure of the program to be optimized is fixed, while its numerical parameters are allowed to evolve.
It was first used by
Lawrence J. Fogel in the US in 1960 in order to use simulated
evolution
Evolution is change in the heritable characteristics of biological populations over successive generations. These characteristics are the expressions of genes, which are passed on from parent to offspring during reproduction. Variation ...
as a learning process aiming to generate
artificial intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech ...
. Fogel used
finite-state machine
A finite-state machine (FSM) or finite-state automaton (FSA, plural: ''automata''), finite automaton, or simply a state machine, is a mathematical model of computation. It is an abstract machine that can be in exactly one of a finite number o ...
s as predictors and evolved them.
Currently evolutionary programming is a wide
evolutionary computing
In computer science, evolutionary computation is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms. In technical terms, th ...
dialect with no fixed structure or (
representation), in contrast with some of the other dialects. It has become harder to distinguish from
evolutionary strategies.
Its main variation operator is
mutation
In biology, a mutation is an alteration in the nucleic acid sequence of the genome of an organism, virus, or extrachromosomal DNA. Viral genomes contain either DNA or RNA. Mutations result from errors during DNA or viral replication, m ...
; members of the population are viewed as part of a specific species rather than members of the same species therefore each parent generates an offspring, using a (μ + μ)
survivor selection.
See also
*
Artificial intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech ...
*
Genetic algorithm
In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to ge ...
*
Genetic operator
References
* Fogel, L.J., Owens, A.J., Walsh, M.J. (1966), ''Artificial Intelligence through Simulated Evolution'', John Wiley.
* Fogel, L.J. (1999), ''Intelligence through Simulated Evolution : Forty Years of Evolutionary Programming'', John Wiley.
* Eiben, A.E., Smith, J.E. (2003)
''Introduction to Evolutionary Computing''Springer
External links
* ttp://www.cleveralgorithms.com/nature-inspired/evolution/evolutionary_programming.html Evolutionary Programming by Jason Brownlee (PhD)
Evolutionary algorithms
Optimization algorithms and methods
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