Evolutionary Computation Glossary

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G

GA:

See GENETIC ALGORITHM.

GAME THEORY:

A mathematical theory originally developed for human games, and generalized to human economics and military strategy, and to EVOLUTION in the theory of EVOLUTIONARILY STABLE STRATEGY. GAME THEORY comes into its own wherever the optimum policy is not fixed, but depends upon the policy which is statistically most likely to be adopted by opponents.

GAMETE:

(biol) Cells which carry genetic information from their PARENTs for the purposes of sexual REPRODUCTION. In animals, male GAMETEs are called sperm, female gametes are called ova. Gametes have a HAPLOID number of CHROMOSOMEs.

GAUSSIAN DISTRIBUTION:

See NORMALLY DISTRIBUTED.

GENE:

(EC) A subsection of a CHROMOSOME which (usually) encodes the value of a single parameter.

(biol) The fundamental unit of inheritance, comprising a segment of DNA that codes for one or several related functions and occupies a fixed position (locus) on the chromosome. However, the term may be defined in different ways for different purposes. For a fuller story, consult a book on genetics (See Q10.7).

GENE-POOL:

The whole set of GENEs in a breeding POPULATION. The metaphor on which the term is based de-emphasizes the undeniable fact that genes actually go about in discrete bodies, and emphasizes the idea of genes flowing about the world like a liquid.

Everybody out of the gene-pool, now!

--- Author prefers to be anonymous

GENERATION:

(EC) An iteration of the measurement of FITNESS and the creation of a new POPULATION by means of REPRODUCTION OPERATORs.

GENETIC ALGORITHM:

A type of EVOLUTIONARY COMPUTATION devised by John Holland [HOLLAND92]. A model of machine learning that uses a genetic/evolutionary metaphor. Implementations typically use fixed-length character strings to represent their genetic information, together with a POPULATION of INDIVIDUALs which undergo CROSSOVER and MUTATION in order to find interesting regions of the SEARCH SPACE. See Q1.1 for more information.

GENETIC DRIFT:

Changes in gene/allele frequencies in a POPULATION over many GENERATIONs, resulting from chance rather than SELECTION. Occurs most rapidly in small populations. Can lead to some ALLELEs becoming `extinct', thus reducing the genetic variability in the population.

GENETIC PROGRAMMING:

GENETIC ALGORITHMs applied to programs. GENETIC PROGRAMMING is more expressive than fixed-length character string GAs, though GAs are likely to be more efficient for some classes of problems. See Q1.5 for more information.

GENETIC OPERATOR:

A search operator acting on a coding structure that is analogous to a GENOTYPE of an organism (e.g. a CHROMOSOME).

GENOTYPE:

The genetic composition of an organism: the information contained in the GENOME.

GENOME:

The entire collection of GENEs (and hence CHROMOSOMEs) possessed by an organism.

GLOBAL OPTIMIZATION:

The process by which a search is made for the extremum (or extrema) of a functional which, in EVOLUTIONARY COMPUTATION, corresponds to the FITNESS or error function that is used to assess the PERFORMANCE of any INDIVIDUAL.

GP:

See GENETIC PROGRAMMING.

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Hitch Hiker's Guide to Evolutionary Computation, Issue 6.4, released 21 December 1998
Copyright © 1993-1998 by J. Heitkötter and D. Beasley, all rights reserved.