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: Guided Self-Organization: Inception
  name:
    name part: Prokopenko, Mikhail.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXII, 475 p. 172 illus., 54 illus. in color. online resource.
  abstract: Is it possible to guide the process of self-organisation towards specific patterns and outcomes? Wouldn’t this be self-contradictory? After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control. Then how can we place the guiding elements so that they do not override rich choices potentially discoverable by an uncontrolled process? This book presents different approaches to resolving this paradox. In doing so, the presented studies address a broad range of phenomena, ranging from autopoietic systems to morphological computation, and from small-world networks to information cascades in swarms. A large variety of methods is employed, from spontaneous symmetry breaking to information dynamics to evolutionary algorithms, creating a rich spectrum reflecting this emerging field. Demonstrating several foundational theories and frameworks, as well as innovative practical implementations, Guided Self-Organisation: Inception, will be an invaluable tool for advanced students and researchers in a multiplicity of fields across computer science, physics and biology, including information theory, robotics, dynamical systems, graph theory, artificial life, multi-agent systems, theory of computation and machine learning.
  table of contents: Foundational frameworks -- Coordinated behaviour and learning within an embodied agent -- Swarms and networks of agents.
  note: edited by Mikhail Prokopenko.
  subject:
    topic: Engineering
  subject:
    topic: Computers
  subject:
    topic: Artificial intelligence
  subject:
    topic: Statistical physics
  subject:
    topic: Computational intelligence
  subject:
    topic: Complexity, Computational
  subject:
    topic: Engineering
  subject:
    topic: Complexity
  subject:
    topic: Theory of Computation
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Computational Intelligence
  subject:
    topic: Nonlinear Dynamics
  classification: QA76.9.M35
  classification: 620
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Emergence, Complexity and Computation, 9
  identifier: 9783642537349
  identifier: http://dx.doi.org/10.1007/978-3-642-53734-9
  record info:
    record creation date: 131219
    record change date: 20151103124353.0
    record identifier: 978-3-642-53734-9