Estimation of distribution algorithm

In evolutionary computation the population may be approximated with a probability distribution over the space of possible solutions. This may have several advantages, including avoiding premature convergence and being a more compact representation.

Better known EDAs include the Compact Genetic Algorithm and the Population Based Incremental Learner.

The model may be found to fit an existing population or take on the role of the population entirely. Once the model is obtained, it can be sampled to produce more candidate solutions which are then used to adapt or regenerate the model.