The Theory of Evolution Strategies
Afbeeldingen
Sla de afbeeldingen overArtikel vergelijken
Auteur:
Hans-Georg Beyer
H. G. Beyer
- Engels
- Hardcover
- 9783540672975
- 27 maart 2001
- 381 pagina's
Samenvatting
Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years.
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.
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.
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.
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.
Productspecificaties
Wij vonden geen specificaties voor jouw zoekopdracht '{SEARCH}'.
Inhoud
- Taal
- en
- Bindwijze
- Hardcover
- Oorspronkelijke releasedatum
- 27 maart 2001
- Aantal pagina's
- 381
- Illustraties
- Nee
Betrokkenen
- Hoofdauteur
- Hans-Georg Beyer
- Tweede Auteur
- H. G. Beyer
- Hoofduitgeverij
- Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Overige kenmerken
- Editie
- 2001 ed.
- Extra groot lettertype
- Nee
- Product breedte
- 159 mm
- Product hoogte
- 27 mm
- Product lengte
- 241 mm
- Studieboek
- Nee
- Verpakking breedte
- 159 mm
- Verpakking hoogte
- 27 mm
- Verpakking lengte
- 241 mm
- Verpakkingsgewicht
- 737 g
EAN
- EAN
- 9783540672975
Je vindt dit artikel in
- Categorieën
- Taal
- Engels
- Boek, ebook of luisterboek?
- Boek
- Beschikbaarheid
- Leverbaar
- Studieboek of algemeen
- Algemene boeken
Kies gewenste uitvoering
Bindwijze
: Hardcover
Prijsinformatie en bestellen
De prijs van dit product is 86 euro en 40 cent. Dit is een tweedehands product.Alleen tweedehands
Goed
Ref4897
Ref4897
1 - 2 weken
Verkoop door
BAY EXPRESS
- Bestellen en betalen via bol
- Prijs inclusief verzendkosten, verstuurd door BAY EXPRESS
- 30 dagen bedenktijd en gratis retourneren
Shop dit artikel
Rapporteer dit artikel
Je wilt melding doen van illegale inhoud over dit artikel:
- Ik wil melding doen als klant
- Ik wil melding doen als autoriteit of trusted flagger
- Ik wil melding doen als partner
- Ik wil melding doen als merkhouder
Geen klant, autoriteit, trusted flagger, merkhouder of partner? Gebruik dan onderstaande link om melding te doen.