EDAspy: An extensible python package for estimation of distribution algorithms

作     者：Soloviev, Vicente P. Larranaga, Pedro Bielza, Concha 

作者机构：Univ Politecn Madrid Artificial Intelligence Dept Campus Montegancedo Madrid Spain 

出 版 物：《NEUROCOMPUTING》 (神经计算)

年 卷 期：2024年第598卷

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Spanish Ministry of Science and Innovation [PID2022-139977NB-I00, TED2021-131310B-I00, FPI PRE2020-094828] Autonomous Community of Madrid within the ELLIS Unit Madrid framework 

主　　题：Estimation of distribution algorithm Evolutionary algorithm Bayesian network Benchmarking 

摘      要：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.