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: Simulating Social Complexity
    sub title: A Handbook
  name:
    name part: Edmonds, Bruce.
    role:
      role term: editor.
  name:
    name part: Meyer, Ruth.
    role:
      role term: editor.
  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: VII, 754 p. online resource.
  abstract: Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society. The phenomena of interest then result (emerge) from the dynamics of the interaction of social actors in an essential way and are usually not easily simplifiable by, for example, considering only representative actors. The introduction of accessible agent-based modelling allows the representation of social complexity in a more natural and direct manner than previous techniques. In particular, it is no longer necessary to distort a model with the introduction of overly strong assumptions simply in order to obtain analytic tractability. This makes agent-based modelling relatively accessible to a range of scientists. The outcomes of such models can be displayed and animated in ways that also make them more interpretable by experts and stakeholders. This handbook is intended to help in the process of maturation of this new field. It brings together, through the collaborative effort of many leading researchers, summaries of the best thinking and practice in this area and constitute…
  table of contents: Introduction -- Methodology -- Mechanisms -- Applictions.
  note: edited by Bruce Edmonds, Ruth Meyer.
  subject:
    topic: Computer science
  subject:
    topic: Computers
  subject:
    topic: Application software
  subject:
    topic: Behavioral sciences
  subject:
    topic: Game theory
  subject:
    topic: Statistical physics
  subject:
    topic: Dynamical systems
  subject:
    topic: Social sciences
  subject:
    topic: Computer Science
  subject:
    topic: Computer Appl. in Social and Behavioral Sciences
  subject:
    topic: Social Sciences, general
  subject:
    topic: Statistical Physics, Dynamical Systems and Complexity
  subject:
    topic: Behavioral Sciences
  subject:
    topic: Game Theory, Economics, Social and Behav. Sciences
  subject:
    topic: Computing Methodologies
  classification: QA76.76.A65
  classification: 004
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Understanding Complex Systems
  identifier: 9783540938132
  identifier: http://dx.doi.org/10.1007/978-3-540-93813-2
  record info:
    record creation date: 130405
    record change date: 20151204165735.0
    record identifier: 978-3-540-93813-2