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].

Contents 1 Genotype representation 2 Algorithm 3 See also 4 References

[edit] 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.

[edit] 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

[edit] See also

• Estimation of Distribution Algorithm

[edit] References

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