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Herausgeber: 
  • Pierre Del Moral
  • Oliver Schütze
  • Carlos A. Coello Coello
  • Pascal Bouvry
  • Pierrick Legrand
  • Alexandru-Adrian Tantar
  • Emilia Tantar
  • EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2014  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / B / Computational Intelligence / engineering / Probability and statistics / Statistics / Wahrscheinlichkeitsrechnung und Statistik
    ISBN:  9783642445033 
    EAN-Code: 
    9783642445033 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #447 - Studies in Computational Intelligence  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  6555 gr 
    Seiten:  414 
    Illustration:  XXII, 414 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The aim of this book is to provide a strong theoretical support for understanding and analyzing the behavior of evolutionary algorithms, as well as for creating a bridge between probability, set-oriented numerics and evolutionary computation.

    The volume encloses a collection of contributions that were presented at the EVOLVE 2011 international workshop, held in Luxembourg, May 25-27, 2011, coming from invited speakers and also from selected regular submissions. The aim of EVOLVE is to unify the perspectives offered by probability, set oriented numerics and evolutionary computation. EVOLVE focuses on challenging aspects that arise at the passage from theory to new paradigms and practice, elaborating on the foundations of evolutionary algorithms and theory-inspired methods merged with cutting-edge techniques that ensure performance guarantee factors. EVOLVE is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background.

    The chapters enclose challenging theoretical findings, concrete optimization problems as well as new perspectives. By gathering contributions from researchers with different backgrounds, the book is expected to set the basis for a unified view and vocabulary where theoretical advancements may echo in different domains.

      



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