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: Self-organizing Coalitions for Managing Complexity
    sub title: Agent-based Simulation of Evolutionary Game Theory Models using Dynamic Social Networks for Interdisciplinary Applications
  name:
    name part: Burguillo, Juan C.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 343 p. 187 illus., 149 illus. in color. online resource.
  abstract: This book provides an interdisciplinary approach to complexity, combining ideas from areas like complex networks, cellular automata, multi-agent systems, self-organization and game theory. The first part of the book provides an extensive introduction to these areas, while the second explores a range of research scenarios. Lastly, the book presents CellNet, a software framework that offers a hands-on approach to the scenarios described throughout the book. In light of the introductory chapters, the research chapters, and the CellNet simulating framework, this book can be used to teach undergraduate and master's students in disciplines like artificial intelligence, computer science, applied mathematics, economics and engineering. Moreover, the book will be particularly interesting for Ph.D. and postdoctoral researchers seeking a general perspective on how to design and create their own models.
  table of contents: Introduction.- Complex Systems -- Complex Networks.- Cellular Automata.- Multi-agent Systems -- Self-Organization.- Game Theory.- Optimization Models with Coalitional Cellular Automata -- Time Series Prediction using Coalitions and Self-Organizing Maps.
  note: by Juan C. Burguillo.
  subject:
    topic: Computational complexity
  subject:
    topic: Computational intelligence
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Physics
  subject:
    topic: Complexity
  subject:
    topic: Computational Intelligence
  subject:
    topic: Operations Research/Decision Theory
  subject:
    topic: Applications of Graph Theory and Complex Networks
  classification: QA267.7
  classification: 620
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Emergence, Complexity and Computation, 29
  identifier: 9783319698984
  identifier: https://doi.org/10.1007/978-3-319-69898-4
  record info:
    record creation date: 171213
    record change date: 20191022054049.0
    record identifier: 978-3-319-69898-4