License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.12.5.17
URN: urn:nbn:de:0030-drops-174421
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/17442/
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Uribe, Josu Ceberio ; Doerr, Benjamin ; Witt, Carsten ; Soloviev, Vicente P.
Weitere Beteiligte (Hrsg. etc.): Josu Ceberio Uribe and Benjamin Doerr and Carsten Witt and Vicente P. Soloviev

Estimation-of-Distribution Algorithms: Theory and Applications (Dagstuhl Seminar 22182)

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dagrep_v012_i005_p017_22182.pdf (2 MB)

Abstract

The Dagstuhl seminar 22182 Estimation-of-Distribution Algorithms: Theory and Practice on May 2-6, 2022 brought together 19 international experts in estimation-of-distribution algorithms (EDAs). Their research ranged from a theoretical perspective, e.g., runtime analysis on synthetic problems, to an applied perspective, e.g., solutions of industrial optimization problems with EDAs. This report documents the program and the outcomes of the seminar.

BibTeX - Entry

@Article{uribe_et_al:DagRep.12.5.17,
  author =	{Uribe, Josu Ceberio and Doerr, Benjamin and Witt, Carsten and Soloviev, Vicente P.},
  title =	{{Estimation-of-Distribution Algorithms: Theory and Applications (Dagstuhl Seminar 22182)}},
  pages =	{17--36},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{12},
  number =	{5},
  editor =	{Uribe, Josu Ceberio and Doerr, Benjamin and Witt, Carsten and Soloviev, Vicente P.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/17442},
  URN =		{urn:nbn:de:0030-drops-174421},
  doi =		{10.4230/DagRep.12.5.17},
  annote =	{Keywords: estimation-of-distribution algorithms, heuristic search and optimization, machine learning, probabilistic model building}
}

Keywords: estimation-of-distribution algorithms, heuristic search and optimization, machine learning, probabilistic model building
Collection: DagRep, Volume 12, Issue 5
Issue Date: 2022
Date of publication: 08.12.2022

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