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Estimation of distribution algorithms (EDAs) are a type of evolutionary algorithms where a probabilistic model is learned and sampled in each iteration. EDAspy provides different state-of-the-art implementations of EDAs including the recent semiparametric EDA. The implementations are modularly built, allowing for easy extension and the selection of different alternatives, as well as interoperability with new components. EDAspy is totally free and open-source under the MIT license.
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Soloviev et al. (2024) studied this question.
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