« Sélection » : différence entre les versions


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== Domaine ==
== Domaine ==
[Category:Vocabulary]]<br/>
 
[[Category:Vocabulary]]<br/>
[[Category:Intelligence artificielle]]Intelligence artificielle<br/>
[[Category:Intelligence artificielle]]Intelligence artificielle<br/>
[[Category:Algorithme génétique]]Algorithme génétique<br/>
[[Category:Coulombe]]Coulombe<br/>
[[Category:Coulombe]]Coulombe<br/>
[[Category:Scotty]]<br/>


== Définition ==
== Définition ==

Version du 12 mai 2019 à 00:34

Domaine


Intelligence artificielle
Algorithme génétique
Coulombe

Définition

La sélection est l'étape d'un algorithme génétique au cours de laquelle des génomes individuels sont choisis dans une population dans le but d'une reproduction ultérieure (à l'aide de l'opérateur de croisement).

Source: https://en.wikipedia.org/wiki/Selection_(genetic_algorithm)

Français

sélection

Anglais

Selection (genetic algorithm)

Selection is the stage of a genetic algorithm in which individual genomes are chosen from a population for later breeding (using the crossover operator).

A generic selection procedure may be implemented as follows:

   The fitness function is evaluated for each individual, providing fitness values, which are then normalized. Normalization means dividing the fitness value of each individual by the sum of all fitness values, so that the sum of all resulting fitness values equals 1.
   The population is sorted by descending fitness values.
   Accumulated normalized fitness values are computed: the accumulated fitness value of an individual is the sum of its own fitness value plus the fitness values of all the previous individuals; the accumulated fitness of the last individual should be 1, otherwise something went wrong in the normalization step.
   A random number R between 0 and 1 is chosen.
   The selected individual is the last one whose accumulated normalized value is smaller than R.

For a large number of individuals the above algorithm might be computationally quite demanding. A simpler and faster alternative uses the so-called stochastic acceptance.