rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Analyzing Evolutionary Algorithms
    sub title: The Computer Science Perspective
  name:
    name part: Jansen, Thomas.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 258 p. online resource.
  abstract: Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years. In this book the author provides an introduction to the methods used to analyze evolutionary algorithms and other randomized search heuristics. He starts with an algorithmic and modular perspective and gives guidelines for the design of evolutionary algorithms. He then places the approach in the broader research context with a chapter on theoretical perspectives. By adopting a complexity-theoretical perspective, he derives general limitations for black-box optimization, yielding lower bounds on the performance of evolutionary algorithms, and then develops general methods for deriving upper and lower bounds step by step. This main part is followed by a chapter covering practical applications of these methods. The notational and mathematical basics are covered in an appendix, the results presented are derived in detail, and each chapter ends with detailed comments and pointers to further reading. So the book is a useful reference for both graduate students and researchers engaged with the theoretical analysis of such algorithms. .
  table of contents: Introduction -- Evolutionary Algorithms and Other Randomized Search Heuristics -- Theoretical Perspectives on Evolutionay Algorithms -- General Limits in Black-Box Optimization -- Methods for the Analysis of Evolutionary Algorithms -- Selected Topics in the Analysis of Evolutionary Algorithms -- App. A, Landau Notation -- App. B, Tail Estimations -- App. C, Martingales and Applications.
  note: by Thomas Jansen.
  subject:
    topic: Computer science
  subject:
    topic: Computers
  subject:
    topic: Artificial intelligence
  subject:
    topic: Mathematical optimization
  subject:
    topic: Computational intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Theory of Computation
  subject:
    topic: Computational Intelligence
  subject:
    topic: Optimization
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: QA75.5-76.95
  classification: 004.0151
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Natural Computing Series
  identifier: 9783642173394
  identifier: http://dx.doi.org/10.1007/978-3-642-17339-4
  record info:
    record creation date: 130125
    record change date: 20151103123317.0
    record identifier: 978-3-642-17339-4