Evolutionary computation

In computer science evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) that involves combinatorial optimization problems. Computer science (or computing science) is the study and the Science of the theoretical foundations of Information and Computation and their Computational intelligence (CI is an offshoot of Artificial intelligence. Combinatorial optimization is a branch of optimization. Its domain is optimization problems where the set of Feasible solutions is discrete or can be reduced

Evolutionary computation uses iterative progress, such as growth or development in a population. In Biology a population is the collection of inter-breeding organisms of a particular Species; in Sociology This population is then selected in a guided random search using parallel processing to achieve the desired end. Artificial selection is the intentional breeding for certain traits or combinations of traits over others and is synonymous with " Selective breeding " Randomness is a lack of order Purpose, cause, or predictability Parallel processing is also another term for Parallel computing. Such processes are often inspired by biological mechanisms of evolution. eVolution is the third Album by eLDee, it was due to be released in 2008

1 History
2 Techniques
3 Evolutionary algorithms
4 Evolutionary computation practitioners
5 Major conferences and workshops
6 Journals
7 See also
8 Bibliography
9 References

History

In the fifties, the idea to use Darwinian principles for automated problem solving originated. The 1950s Decade refers to the years of 1950 to 1959 inclusive Darwinism is a term used for various different movements or concepts related to a greater or lesser extent to Charles Darwin 's work on Evolution. It was not until the sixties that three distinct interpretations of this idea started to be developed in three different places. The 1960s decade refers to the years from the beginning of 1960 to the end of 1969

Evolutionary programming was introduced by Lawrence J. Fogel in the USA, while John Henry Holland called his method a genetic algorithm. Evolutionary programming is one of the four major Evolutionary algorithm paradigms Dr Lawrence J Fogel (March 2 1928 - February 18 2007 was a pioneer in Evolutionary computation and human factors analysis The United States of America —commonly referred to as the John Henry Holland ( 2 February, 1929) is an American scientist and Professor of Psychology and Professor of Electrical Engineering and Computer A genetic algorithm (GA is a Search technique used in Computing to find exact or Approximate solutions to optimization and Search In Germany Ingo Rechenberg and Hans-Paul Schwefel introduced evolution strategies. Germany, officially the Federal Republic of Germany ( ˈbʊndəsʁepuˌbliːk ˈdɔʏtʃlant is a Country in Central Europe. Ingo Rechenberg (born January 20 1934 in Berlin) is a German computer scientist and professor Hans-Paul Schwefel (born December 4, 1940 in Berlin) is a German Computer scientist and professor emeritus at University of Dortmund In computer science evolution strategy (ES is an optimization technique based on ideas of adaptation and evolution These areas developed separately for about 15 years. From the early nineties on they are unified as different representatives (“dialects”) of one technology, called evolutionary computing. The 1990s collectively refers to the years between and including 1990 and 1999 Also in the early nineties, a fourth stream following the general ideas had emerged – genetic programming. In Artificial intelligence, genetic programming (GP is an Evolutionary algorithm based methodology inspired by Biological evolution to find

These terminologies denote the field of evolutionary computing and consider evolutionary programming, evolution strategies, genetic algorithms, and genetic programming as sub-areas.

Techniques

Evolutionary techniques mostly involve metaheuristic optimization algorithms such as:

evolutionary algorithms (comprising genetic algorithms, evolutionary programming, evolution strategy, genetic programming and learning classifier systems)
swarm intelligence (comprising ant colony optimization and particle swarm optimization)

and in a lesser extent also:

self-organization such as self-organizing maps, growing neural gas, competitive learning demo applet
differential evolution
artificial life (also see digital organism)
cultural algorithms
harmony search algorithm
artificial immune systems
Learnable Evolution Model

Evolutionary algorithms

Main article: evolutionary algorithm

Evolutionary algorithms form a subset of evolutionary computation in that they generally only involve techniques implementing mechanisms inspired by biological evolution such as reproduction, mutation, recombination, natural selection and survival of the fittest. A metaheuristic is a Heuristic method for solving a very general class of computational problems by combining user-given black-box procedures ��usually heuristics In Computing, optimization is the process of modifying a system to make some aspect of it work more efficiently or use fewer resources In Mathematics, Computing, Linguistics and related subjects an algorithm is a sequence of finite instructions often used for Calculation In Artificial intelligence, an evolutionary algorithm (EA is a Subset of Evolutionary computation, a generic population-based Metaheuristic A genetic algorithm (GA is a Search technique used in Computing to find exact or Approximate solutions to optimization and Search Evolutionary programming is one of the four major Evolutionary algorithm paradigms In computer science evolution strategy (ES is an optimization technique based on ideas of adaptation and evolution In Artificial intelligence, genetic programming (GP is an Evolutionary algorithm based methodology inspired by Biological evolution to find A learning classifier system, or LCS is a Machine learning system with close links to Reinforcement learning and Genetic algorithms. Swarm intelligence (SI is Artificial intelligence based on the Collective behavior of decentralized, self-organized systems The ant colony optimization Algorithm (ACO introduced by Marco Dorigo in 1992 in his PhD thesis is a probabilistic technique for solving computational Particle swarm optimization (PSO is a Swarm intelligence based Algorithm to find a solution to an optimization problem in a Search space, or model and Self-organization is a process of Attraction and repulsion in which the internal organization of a System, normally an open system, increases A self-organizing map (SOM is a type of Artificial neural network that is trained using Unsupervised learning to produce a low-dimensional (typically two dimensional Growing Neural Gas is a self organization neural network first proposed by Bernd Fritzke Differential Evolution (DE is a method of mathematical optimization of multidimensional functions and belongs to the class of Evolution strategy optimizers Artificial life (commonly Alife or alife) is a field of study and an associated art form which examine Systems related to Life, its processes A digital organism is a self-replicating Computer program that mutates and evolves. 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 Harmony search (HS is a Metaheuristic algorithm (also known as Soft computing algorithm or Evolutionary algorithm) mimicking the improvisation process Artificial immune systems (AIS are computational systems inspired by the principles and processes of the vertebrate Immune system. The Learnable Evolution Model (LEM is a novel non- Darwinian methodology for Evolutionary computation that employs Machine learning to guide the generation In Artificial intelligence, an evolutionary algorithm (EA is a Subset of Evolutionary computation, a generic population-based Metaheuristic In Artificial intelligence, an evolutionary algorithm (EA is a Subset of Evolutionary computation, a generic population-based Metaheuristic eVolution is the third Album by eLDee, it was due to be released in 2008 Reproduction is the Biological process by which new individual Organisms are produced In biology mutations are changes to the Nucleotide sequence of the Genetic material of an organism Natural selection is the process by which favorable Heritable traits become more common in successive Generations of a Population of "Survival of the fittest" is a Phrase which is shorthand for a concept relating to competition for survival or predominance Candidate solutions to the optimization problem play the role of individuals in a population, and the cost function determines the environment within which the solutions "live" (see also fitness function). In optimization (a branch of Mathematics) a candidate solution is a member of a set of possible solutions to a given problem In Mathematics, the term optimization, or mathematical programming, refers to the study of problems in which one seeks to minimize or maximize a real function A fitness function is a particular type of Objective function that quantifies the optimality of a solution (that is a chromosome) in a Genetic algorithm Evolution of the population then takes place after the repeated application of the above operators. eVolution is the third Album by eLDee, it was due to be released in 2008

In this process, there are two main forces that form the basis of evolutionary systems: Recombination and mutation create the necessary diversity and thereby facilitate novelty, while selection acts as a force increasing quality.

Many aspects of such an evolutionary process are stochastic. Stochastic (from the Greek "Στόχος" for "aim" or "guess" means Random. Changed pieces of information due to recombination and mutation are randomly chosen. On the other hand, selection operators can be either deterministic, or stochastic. In the latter case, individuals with a higher fitness have a higher chance to be selected than individuals with a lower fitness, but typically even the weak individuals have a chance to become a parent or to survive.