Theory of estimation-of-distribution algorithms

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

17 Downloads (Pure)

Abstract

Summary Runtime analysis for simple univariate EDAs Identified similarities to and differences from simple EAs Genetic drift a major obstacle Sensitive to parameters (phase transitions) Robust to noise Significance-based EDAs as novel theory-driven approach Future work Combinatorial problems Multivariate EDAs Classification of problems w. r. t. appropriateness for EAs/EDAs.
Original languageEnglish
Title of host publicationProceedings of 2019 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Publication date2019
Pages1197-1225
ISBN (Print)9781450367486
DOIs
Publication statusPublished - 2019
Event2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Conference

Conference2019 Genetic and Evolutionary Computation Conference, GECCO 2019
CountryCzech Republic
CityPrague
Period13/07/201917/07/2019
SponsorAssociation for Computing Machinery

Cite this

Witt, C. (2019). Theory of estimation-of-distribution algorithms. In Proceedings of 2019 Genetic and Evolutionary Computation Conference (pp. 1197-1225). Association for Computing Machinery. https://doi.org/10.1145/3319619.3323367