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Population-based incremental learning

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In machine learning and soft computing, population-based incremental learning (PBIL) is a type of genetic algorithm where the genotype of an entire population is evolved rather than individual members[1].

Genotype representation

In PBIL, genes are represented as real values in the range [0,1], indicating the probability that any particular allele appears in that gene.

Algorithm

The PBIL algorithm is as follows:

  1. A population is generated.
  2. The fitness of each member is evaluated and ranked.
  3. Update population genotype based on fittest individual.
  4. Repeat steps 2-3

See also

References

  1. ^ Karray, Fakhreddine O.; de Silva, Clarence (2004), Soft computing and intelligent systems design, Addison Wesley, ISBN 0-321-11617-8
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