The Theory of Evolution Strategies:
Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields,...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2001
|
| Ausgabe: | 1st ed. 2001 |
| Schriftenreihe: | Natural Computing Series
|
| Schlagwörter: | |
| Links: | https://doi.org/10.1007/978-3-662-04378-3 https://doi.org/10.1007/978-3-662-04378-3 |
| Zusammenfassung: | Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much. This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work |
| Umfang: | 1 Online-Ressource (XX, 381 p) |
| ISBN: | 9783662043783 |
| DOI: | 10.1007/978-3-662-04378-3 |
Internformat
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Datensatz im Suchindex
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| dewey-full | 006.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Biologie Informatik |
| doi_str_mv | 10.1007/978-3-662-04378-3 |
| edition | 1st ed. 2001 |
| format | Electronic eBook |
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| id | DE-604.BV047064903 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:08:45Z |
| institution | BVB |
| isbn | 9783662043783 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032472015 |
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| physical | 1 Online-Ressource (XX, 381 p) |
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| publishDate | 2001 |
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| publisher | Springer Berlin Heidelberg |
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| series2 | Natural Computing Series |
| spelling | Beyer, Hans-Georg Verfasser aut The Theory of Evolution Strategies by Hans-Georg Beyer 1st ed. 2001 Berlin, Heidelberg Springer Berlin Heidelberg 2001 1 Online-Ressource (XX, 381 p) txt rdacontent c rdamedia cr rdacarrier Natural Computing Series Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much. This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work Artificial Intelligence Programming Techniques Algorithm Analysis and Problem Complexity Complex Systems Computer Appl. in Life Sciences Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial intelligence Computer programming Algorithms Statistical physics Dynamical systems Bioinformatics Computational biology Statistics Evolutionsstrategie (DE-588)4015930-9 gnd rswk-swf Evolutionsstrategie (DE-588)4015930-9 s DE-604 Erscheint auch als Druck-Ausgabe 9783642086700 Erscheint auch als Druck-Ausgabe 9783540672975 Erscheint auch als Druck-Ausgabe 9783662043790 https://doi.org/10.1007/978-3-662-04378-3 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Beyer, Hans-Georg The Theory of Evolution Strategies Artificial Intelligence Programming Techniques Algorithm Analysis and Problem Complexity Complex Systems Computer Appl. in Life Sciences Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial intelligence Computer programming Algorithms Statistical physics Dynamical systems Bioinformatics Computational biology Statistics Evolutionsstrategie (DE-588)4015930-9 gnd |
| subject_GND | (DE-588)4015930-9 |
| title | The Theory of Evolution Strategies |
| title_auth | The Theory of Evolution Strategies |
| title_exact_search | The Theory of Evolution Strategies |
| title_full | The Theory of Evolution Strategies by Hans-Georg Beyer |
| title_fullStr | The Theory of Evolution Strategies by Hans-Georg Beyer |
| title_full_unstemmed | The Theory of Evolution Strategies by Hans-Georg Beyer |
| title_short | The Theory of Evolution Strategies |
| title_sort | the theory of evolution strategies |
| topic | Artificial Intelligence Programming Techniques Algorithm Analysis and Problem Complexity Complex Systems Computer Appl. in Life Sciences Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial intelligence Computer programming Algorithms Statistical physics Dynamical systems Bioinformatics Computational biology Statistics Evolutionsstrategie (DE-588)4015930-9 gnd |
| topic_facet | Artificial Intelligence Programming Techniques Algorithm Analysis and Problem Complexity Complex Systems Computer Appl. in Life Sciences Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial intelligence Computer programming Algorithms Statistical physics Dynamical systems Bioinformatics Computational biology Statistics Evolutionsstrategie |
| url | https://doi.org/10.1007/978-3-662-04378-3 |
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