SettingsGenetic algorithms
Chromosome (genetic algorithm)
In genetic algorithms, a chromosome (also sometimes called a genome) is a set of parameters which define a proposed solution to the problem that the genetic algorithm is trying to solve.
In genetic algorithms, a chromosome (also sometimes called a genome) is a set of parameters which define a proposed solution to the problem that the genetic algorithm is trying to solve.
Clonal Selection Algorithm
In Artificial immune systems, Clonal selection algorithms are a class of algorithms inspired by the clonal selection theory of acquired immunity that explains how B and T lymphocytes improve the...
In Artificial immune systems, Clonal selection algorithms are a class of algorithms inspired by the clonal selection theory of acquired immunity that explains how B and T lymphocytes improve the...
Crossover (genetic algorithm)
In genetic algorithms, crossover is a genetic operator used to vary the programming of a chromosome or chromosomes from one generation to the next.
In genetic algorithms, crossover is a genetic operator used to vary the programming of a chromosome or chromosomes from one generation to the next.
Cultural algorithm
Cultural algorithms (CA) are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to the population component.
Cultural algorithms (CA) are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to the population component.
Defining length
In genetic algorithms and genetic programming defining length L is the maximum distance between two defining symbols in schema H. In tree GP schemata, L is the number of links in the minimum tre...
In genetic algorithms and genetic programming defining length L is the maximum distance between two defining symbols in schema H. In tree GP schemata, L is the number of links in the minimum tre...
Edge recombination operator
The edge recombination operator (ERO) is an operator that creates a path that is similar to a set of existing paths (parents) by looking at the edges rather than the vertices.
The edge recombination operator (ERO) is an operator that creates a path that is similar to a set of existing paths (parents) by looking at the edges rather than the vertices.
Evolver (software)
Evolver is a software package that allows users to solve a wide variety of optimization problems using a genetic algorithm.
Evolver is a software package that allows users to solve a wide variety of optimization problems using a genetic algorithm.
Fitness approximation
In function optimization, fitness approximation is a method for decreasing the number of fitness function evaluations to reach a target solution.
In function optimization, fitness approximation is a method for decreasing the number of fitness function evaluations to reach a target solution.
Fitness function
A fitness function is a particular type of objective function that prescribes the optimality of a solution (that is, a chromosome) in a genetic algorithm so that the particular chromosome may be...
A fitness function is a particular type of objective function that prescribes the optimality of a solution (that is, a chromosome) in a genetic algorithm so that the particular chromosome may be...
Fitness proportionate selection
Fitness proportionate selection, also known as roulette-wheel selection, is a genetic operator used in genetic algorithms for selecting potentially useful solutions for recombination.
Fitness proportionate selection, also known as roulette-wheel selection, is a genetic operator used in genetic algorithms for selecting potentially useful solutions for recombination.
Genetic algorithm
In the computer science field of artificial intelligence, a genetic algorithm is a search heuristic that mimics the process of natural evolution.
In the computer science field of artificial intelligence, a genetic algorithm is a search heuristic that mimics the process of natural evolution.
Genetic algorithms in economics
Genetic algorithms have increasingly been applied to economics over the last two decades.
Genetic algorithms have increasingly been applied to economics over the last two decades.
Genetic fuzzy systems
Genetic fuzzy systems are fuzzy systems using a genetic algorithm for determining the system parameters.
Genetic fuzzy systems are fuzzy systems using a genetic algorithm for determining the system parameters.
Genetic memory (computer science)
In computer science, genetic memory refers to an artificial neural network combination of genetic algorithm and the mathematical model of sparse distributed memory.
In computer science, genetic memory refers to an artificial neural network combination of genetic algorithm and the mathematical model of sparse distributed memory.
Genetic operator
A genetic operator is an operator used in genetic algorithms to maintain genetic diversity, known as Mutation (genetic algorithm) and to combine existing solutions into others, Crossover (geneti...
A genetic operator is an operator used in genetic algorithms to maintain genetic diversity, known as Mutation (genetic algorithm) and to combine existing solutions into others, Crossover (geneti...
Genetic programming
In artificial intelligence, genetic programming is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task.
In artificial intelligence, genetic programming is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task.
Holland's schema theorem
Holland's schema theorem is widely taken to be the foundation for explanations of the power of genetic algorithms.
Holland's schema theorem is widely taken to be the foundation for explanations of the power of genetic algorithms.
HyperNEAT
Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (...
Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (...
Inheritance (genetic algorithm)
In genetic algorithms, inheritance is the ability of modelled objects to mate, mutate and propagate their problem solving genes to the next generation, in order to produce an evolved solution to...
In genetic algorithms, inheritance is the ability of modelled objects to mate, mutate and propagate their problem solving genes to the next generation, in order to produce an evolved solution to...
Mutation (genetic algorithm)
In genetic algorithms of computing, mutation is a genetic operator used to maintain genetic diversity from one generation of a population of algorithm chromosomes to the next.
In genetic algorithms of computing, mutation is a genetic operator used to maintain genetic diversity from one generation of a population of algorithm chromosomes to the next.
Neuroevolution of augmenting topologies
NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Ken Stanley in 200...
NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Ken Stanley in 200...
Parallel metaheuristic
ParadisEO is a white-box object-oriented framework dedicated to the flexible design of metaheuristics.
ParadisEO is a white-box object-oriented framework dedicated to the flexible design of metaheuristics.
Population-based incremental learning
In computer science and machine learning, population-based incremental learning (PBIL) is an optimization algorithm, and an estimation of distribution algorithm.
In computer science and machine learning, population-based incremental learning (PBIL) is an optimization algorithm, and an estimation of distribution algorithm.
Premature convergence
In genetic algorithms, the term of premature convergence means that a population for an optimization problem converged too early, resulting in being suboptimal.
In genetic algorithms, the term of premature convergence means that a population for an optimization problem converged too early, resulting in being suboptimal.
Promoter based genetic algorithm
The promoter based genetic algorithm (PBGA) is a genetic algorithm for neuroevolution developed by F. Bellas and R.J. Duro in the Integrated Group for Engineering Research (GII) at the Uni...
The promoter based genetic algorithm (PBGA) is a genetic algorithm for neuroevolution developed by F. Bellas and R.J. Duro in the Integrated Group for Engineering Research (GII) at the Uni...
Quality control and genetic algorithms
The combination of quality control and genetic algorithms led to novel solutions of complex quality control design and optimization problems.
The combination of quality control and genetic algorithms led to novel solutions of complex quality control design and optimization problems.
Reward-based selection
Reward-based selection is a technique used in evolutionary algorithms for selecting potentially useful solutions for recombination.
Reward-based selection is a technique used in evolutionary algorithms for selecting potentially useful solutions for recombination.
Santa Fe Trail problem
The Santa Fe Trail problem is a Genetic programming exercise in which Artificial Ants search for food pellets according to a programmed set of instructions.
The Santa Fe Trail problem is a Genetic programming exercise in which Artificial Ants search for food pellets according to a programmed set of instructions.
Schema (genetic algorithms)
A schema is a template in computer science used in the field of genetic algorithms that identifies a subset of strings with similarities at certain string positions.
A schema is a template in computer science used in the field of genetic algorithms that identifies a subset of strings with similarities at certain string positions.
Search-based software engineering
Search-based software engineering (SBSE) is an approach to apply metaheuristic search techniques like genetic algorithms, simulated annealing and tabu search to software engineering problems.
Search-based software engineering (SBSE) is an approach to apply metaheuristic search techniques like genetic algorithms, simulated annealing and tabu search to software engineering problems.
Selection (genetic algorithm)
Selection is the stage of a genetic algorithm in which individual genomes are chosen from a population for later breeding (recombination or crossover).
Selection is the stage of a genetic algorithm in which individual genomes are chosen from a population for later breeding (recombination or crossover).
Speciation (genetic algorithm)
Speciation is a process that occurs naturally in evolution and is modeled explicitly in some genetic algorithms.
Speciation is a process that occurs naturally in evolution and is modeled explicitly in some genetic algorithms.
Stochastic universal sampling
Stochastic universal sampling (SUS) is a technique used in genetic algorithms for selecting potentially useful solutions for recombination.
Stochastic universal sampling (SUS) is a technique used in genetic algorithms for selecting potentially useful solutions for recombination.
Tournament selection
Tournament selection is a method of selecting an individual from a population of individuals in a genetic algorithm.
Tournament selection is a method of selecting an individual from a population of individuals in a genetic algorithm.
Truncation selection
Truncation selection is a selection method used in genetic algorithms to select potential candidate solutions for recombination.
Truncation selection is a selection method used in genetic algorithms to select potential candidate solutions for recombination.
Weasel program
The weasel program, Dawkins' weasel, or the Dawkins weasel is a thought experiment and a variety of computer simulations illustrating it.
The weasel program, Dawkins' weasel, or the Dawkins weasel is a thought experiment and a variety of computer simulations illustrating it.