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Gene Expression Programming
In computer programming, gene expression programming (GEP) 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. And like living organisms, the computer programs of GEP are also encoded in simple linear chromosomes of fixed length. Thus, GEP is a genotype–phenotype system, benefiting from a simple genome to keep and transmit the genetic information and a complex phenotype to explore the environment and adapt to it. Background Evolutionary algorithms use populations of individuals, select individuals according to fitness, and introduce genetic variation using one or more genetic operators. Their use in artificial computational systems dates back to the 1950s where they were used to solve optimization problems (e.g. Box 1957 and Friedman 1959). But it was with the introduction of evolution strategies by Rechenber ...
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Computer Programming
Computer programming is the process of performing a particular computation (or more generally, accomplishing a specific computing result), usually by designing and building an executable computer program. Programming involves tasks such as analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms (usually in a chosen programming language, commonly referred to as coding). The source code of a program is written in one or more languages that are intelligible to programmers, rather than machine code, which is directly executed by the central processing unit. The purpose of programming is to find a sequence of instructions that will automate the performance of a task (which can be as complex as an operating system) on a computer, often for solving a given problem. Proficient programming thus usually requires expertise in several different subjects, including knowledge of the application domain, specialized algori ...
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GEP Expression Tree, K-expression Q*-+abcd
GEP may refer to: * Gene expression programming * Giant Electric Pea, a British music label * Gifted Education Programme (Singapore) * Global Environmental Politics, a scholarly journal * Global Entrepreneur Programme, of the UK government * Good engineering practice * Growth elasticity of poverty * Good Epidemiological Practices * Generation expansion planning Generation expansion planning (also known as GEP) is finding an optimal solution for the planning problem in which the installation of new generation units satisfies both technical and financial limits.Kazemi, Hamidreza Moayed, Sahand Ghaseminejad ...
, in power engineering {{disambiguation ...
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Reproduction With Modification
Reproduction (or procreation or breeding) is the biological process by which new individual organisms – "offspring" – are produced from their "parent" or parents. Reproduction is a fundamental feature of all known life; each individual organism exists as the result of reproduction. There are two forms of reproduction: asexual and sexual. In asexual reproduction, an organism can reproduce without the involvement of another organism. Asexual reproduction is not limited to single-celled organisms. The cloning of an organism is a form of asexual reproduction. By asexual reproduction, an organism creates a genetically similar or identical copy of itself. The evolution of sexual reproduction is a major puzzle for biologists. The two-fold cost of sexual reproduction is that only 50% of organisms reproduce and organisms only pass on 50% of their genes.John Maynard Smith ''The Evolution of Sex'' 1978. Sexual reproduction typically requires the sexual interaction of two specializ ...
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Selection And Elitism
Selection may refer to: Science * Selection (biology), also called natural selection, selection in evolution ** Sex selection, in genetics ** Mate selection, in mating ** Sexual selection in humans, in human sexuality ** Human mating strategies, in human sexuality * Social selection, within social groups * Selection (linguistics), the ability of predicates to determine the semantic content of their arguments * Selection in schools, the admission of students on the basis of selective criteria * Selection effect, a distortion of data arising from the way that the data are collected * A selection, or choice function, a function that selects an element from a set Religion * Divine selection, selection by God * Papal selection, selection by clergy Computing * Selection (user interface) ** X Window selection * Selection (genetic algorithm) * Selection (relational algebra) * Selection-based search, a search engine system in which the user invokes a search query using only th ...
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Expression Of A Multicellular GEP System With 3 ADFs And 2 Main Programs
Expression may refer to: Linguistics * Expression (linguistics), a word, phrase, or sentence * Fixed expression, a form of words with a specific meaning * Idiom, a type of fixed expression * Metaphorical expression, a particular word, phrase, or form of words that has a different meaning than its literal form * Expression (sign language), the expressions and postures of the face and body that contribute to the formation of words when signing Symbolic expression * Expression (architecture), implies a clear and authentic displaying of the character or personality of an individual person * Expression (mathematics), a finite combination of symbols that are well-formed according to applicable rules * Expression (computer science), an instruction to execute something that will return a value * Regular expression, a means of matching strings of text in computing * Expression marks, in music, notating the musical dynamics * Symbolic computation expression * S-expression Bodily ex ...
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Recursion (computer Science)
In computer science, recursion is a method of solving a computational problem where the solution depends on solutions to smaller instances of the same problem. Recursion solves such recursive problems by using functions that call themselves from within their own code. The approach can be applied to many types of problems, and recursion is one of the central ideas of computer science. Most computer programming languages support recursion by allowing a function to call itself from within its own code. Some functional programming languages (for instance, Clojure) do not define any looping constructs but rely solely on recursion to repeatedly call code. It is proved in computability theory that these recursive-only languages are Turing complete; this means that they are as powerful (they can be used to solve the same problems) as imperative languages based on control structures such as and . Repeatedly calling a function from within itself may cause the call stack to have a ...
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Expression Of A Unicellular GEP System With Three ADFs
Expression may refer to: Linguistics * Expression (linguistics), a word, phrase, or sentence * Fixed expression, a form of words with a specific meaning * Idiom, a type of fixed expression * Metaphorical expression, a particular word, phrase, or form of words that has a different meaning than its literal form * Expression (sign language), the expressions and postures of the face and body that contribute to the formation of words when signing Symbolic expression * Expression (architecture), implies a clear and authentic displaying of the character or personality of an individual person * Expression (mathematics), a finite combination of symbols that are well-formed according to applicable rules * Expression (computer science), an instruction to execute something that will return a value * Regular expression, a means of matching strings of text in computing * Expression marks, in music, notating the musical dynamics * Symbolic computation expression * S-expression Bodily ex ...
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Gene Expression Programming
In computer programming, gene expression programming (GEP) 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. And like living organisms, the computer programs of GEP are also encoded in simple linear chromosomes of fixed length. Thus, GEP is a genotype–phenotype system, benefiting from a simple genome to keep and transmit the genetic information and a complex phenotype to explore the environment and adapt to it. Background Evolutionary algorithms use populations of individuals, select individuals according to fitness, and introduce genetic variation using one or more genetic operators. Their use in artificial computational systems dates back to the 1950s where they were used to solve optimization problems (e.g. Box 1957 and Friedman 1959). But it was with the introduction of evolution strategies by Rechenber ...
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Expression Of 3 GEP Genes, 1st K-expression *Qb+*-bbba
Expression may refer to: Linguistics * Expression (linguistics), a word, phrase, or sentence * Fixed expression, a form of words with a specific meaning * Idiom, a type of fixed expression * Metaphorical expression, a particular word, phrase, or form of words that has a different meaning than its literal form * Expression (sign language), the expressions and postures of the face and body that contribute to the formation of words when signing Symbolic expression * Expression (architecture), implies a clear and authentic displaying of the character or personality of an individual person * Expression (mathematics), a finite combination of symbols that are well-formed according to applicable rules * Expression (computer science), an instruction to execute something that will return a value * Regular expression, a means of matching strings of text in computing * Expression marks, in music, notating the musical dynamics * Symbolic computation expression * S-expression Bodily ex ...
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Crossover (genetic Algorithm)
In genetic algorithms and evolutionary computation, crossover, 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 reproduction in biology. Solutions can also be generated by cloning an existing solution, which is analogous to asexual reproduction. Newly generated solutions are typically mutated before being added to the population. Different algorithms in evolutionary computation may use different data structures to store genetic information, and each genetic representation can be recombined with different crossover operators. Typical data structures that can be recombined with crossover are bit arrays, vectors of real numbers, or trees. Examples Traditional genetic algorithms store genetic information in a chromosome represented by a bit array. Crossover m ...
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Mutation (genetic Algorithm)
Mutation is a genetic operator used to maintain genetic diversity from one generation of a population of genetic algorithm chromosomes to the next. It is analogous to biological mutation. The classic example of a mutation operator 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. This random variable tells whether or not a particular bit will be flipped. This mutation procedure, based on the biological point mutation, is called single point mutation. Other types are inversion and floating point mutation. When the gene encoding is restrictive as in permutation problems, mutations are swaps, inversions, and scrambles. The purpose of mutation in GAs is to introduce diversity into the sampled population. Mutation operators are used in an attempt to avoid local minima by preventing the population of chromosomes ...
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Genetic Operator
A genetic operator is an operator used in genetic algorithms to guide the algorithm towards a solution to a given problem. There are three main types of operators (mutation, crossover and selection), which must work in conjunction with one another in order for the algorithm to be successful. Genetic operators are used to create and maintain genetic diversity (mutation operator), combine existing solutions (also known as chromosomes) into new solutions (crossover) and select between solutions (selection). In his book discussing the use of genetic programming for the optimization of complex problems, computer scientist John Koza has also identified an 'inversion' or 'permutation' operator; however, the effectiveness of this operator has never been conclusively demonstrated and this operator is rarely discussed. Mutation (or mutation-like) operators are said to be '' unary'' operators, as they only operate on one chromosome at a time. In contrast, crossover operators are said to be ...
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