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Encyclopedia > Evolutionary computation
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In computer science evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) involving combinatorial optimization problems. Image File history File links Portal. ... Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. ... // Hondas intelligent humanoid robot AI redirects here. ... Computational intelligence (CI) is a branch of the study of artificial intelligence. ... Combinatorial optimization is a branch of optimization in applied mathematics and computer science, related to operations research, algorithm theory and computational complexity theory. ...

Whereas evolutionary algorithms generally only involve techniques implementing mechanisms such as reproduction, mutation, recombination, natural selection and survival of the fittest, evolutionary computation can be loosely recognised by the following criteria: An evolutionary algorithm (also EA, evolutionary computation, artificial evolution) is a generic term used to indicate any population-based optimization algorithm that uses mechanisms inspired by biological evolution, such as reproduction, mutation and recombination (see genetic operators). ... For other uses, see Reproduction (disambiguation) Reproduction is the biological process by which new individual organisms are produced. ... In biology, mutations are changes to the genetic material (either DNA or RNA). ... Recombination usually denotes a genetic event that occurs during the formation of sperm and egg cells (especially in areas of study of biology topics). ... Natural selection is the process by which individual organisms with favorable traits are more likely to survive and reproduce. ... Herbert Spencer coined the phrase survival of the fittest Survival of the fittest is a phrase which is a shorthand for a concept relating to competition for survival or predominance. ...

This mostly involves metaheuristic optimization algorithms such as: Look up evolution in Wiktionary, the free dictionary. ... // About Bees This article is about completely random and illogical things. ... Parallel processing is the ability of the brain to simultaneously process incoming stimuli. ... A metaheuristic is a heuristic method for solving a very general class of computational problems by combining user given black-box procedures — usually heuristics themselves — in a hopefully efficient way. ... It has been suggested that Loop optimization be merged into this article or section. ... Flowcharts are often used to graphically represent algorithms. ...

and in a lesser extent also: An evolutionary algorithm (also EA, artificial evolution, AE) indicates a subset of evolutionary computation, which is a part of artificial intelligence. ... A genetic algorithm (abbreviated as GA) is a search technique used in computing (with applications in computer science, engineering, economics, physics, mathematics and other fields) to find true or approximate solutions to optimization and search problems. ... It is a subset of Evolutionary algorithm. ... In computer science, Evolution strategy (ES, from German Evolutionsstrategie) is an optimization technique based on ideas of adaptation and evolution. ... Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. ... A learning classifier system, or LCS, is a machine learning system with close links to reinforcement learning and genetic algorithms. ... Swarm intelligence (SI) is an artificial intelligence technique based around the study of collective behavior in decentralized, self-organized systems. ... The ant colony optimization algorithm (ACO), introduced by Moyson and Manderick [MoMa88] and widely developped by Marco Dorigo [CMD91,Dor92,DoSt04], is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. ... Particle swarm optimization (PSO) is a form of swarm intelligence. ...


Self-organization refers to a process in which the internal organization of a system, normally an open system, increases automatically without being guided or managed by an outside source. ... The self-organizing map (SOM) is a subtype of artificial neural networks. ... Growing Neural Gas is a self organization neural network first proposed by Bernd Fritzke. ... Differential Evolution (DE) grew out of Kenneth Prices attempts to solve the Chebyshev polynomial fitting problem that had been posed to him by Rainer Storn. ... Artificial life, also known as alife or a-life, is the study of life through the use of human-made analogs of living systems. ... A digital organism is a self-replicating computer program that mutates and evolves. ... Artificial Immune Systems (AIS) are computer algorithms inspired by the principles and processes of the vertebrates immune system. ... This article or section may contain original research or unverified claims. ...

Related topics

Interactive evolutionary computation (IEC) or Aesthetic Selection is a general term for methods of evolutionary computation that use human evaluation. ... Human-based evolutionary computation (HBEC) is a set of evolutionary computation techniques that rely on human innovation. ...

Major Conferences and Workshops

The IEEE Congress on Evolutionary Computation (CEC) is one of the largest and most important conferences within Evolutionary computation (EC), the other conferences of similar importance being Genetic and Evolutionary Computation Conference (GECCO) and Parallell Problem Solving from Nature (PPSN). ...



  Results from FactBites:
Criticisms of Evolutionary Computation - Draft paper (2534 words)
All evolutionary computation is premised upon a "genetic" representation of either a candidate solution for an optimization problem (as in GAs) or an instantiation of a program to be "run" on a virtual or real machine (AL and GP).
Computer simulation, once held to be either a potential indicator of merit or an actual falsifier of natural selection, is then treated as essentially irrelevant to natural selection.
It is certainly true that computer simulations are less complex than biological problems, but the claim at issue is not that EC captures all the nuances of biology, but rather that EC gives a demonstration of the adaptive capabilities of natural selection as an algorithm.
  More results at FactBites »



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