Drift and Scaling in Estimation of Distribution Algorithms

  title={Drift and Scaling in Estimation of Distribution Algorithms},
  author={Jonathan L. Shapiro},
  journal={Evolutionary Computation},
This paper considers a phenomenon in Estimation of Distribution Algorithms (EDA) analogous to drift in population genetic dynamics. Finite population sampling in selection results in fluctuations which get reinforced when the probability model is updated. As a consequence, any probability model which can generate only a single set of values with probability 1 can be an attractive fixed point of the algorithm. To avoid this, parameters of the algorithm must scale with the system size in strongly… CONTINUE READING
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