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: Decision Systems and Nonstochastic Randomness
  name:
    name part: Ivanenko, V. I.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2010
    edition: 1.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 272 p. online resource.
  abstract: “Decision Systems and Nonstochastic Randomness” presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for the description of uncertain mass events that do not fit standard stochastic models. Each self-contained chapter of this neatly-structured monograph includes a detailed introduction and summary of its contents. The included results are presented not only with rigorous proofs but also through numerous intuitive examples. An appendix is provided which includes classic results from the theory of functions and measured sets as well as decision theory, offering an overview of the necessary prerequisites. The formalism of statistical regularities developed in this book will have a significant influence on decision theory and information theory as well as numerous other disciplines. Because of these far-reaching implications, this book may be a useful resource for statisticians, mathematicians, engineers, economists and other utilizing nonstochastic modeling and decision theory.
  table of contents: Decision Systems -- Indifferent Uncertainty -- Nonstochastic Randomness -- General Decision Problems -- Experiment in Decision Problems -- Informativity of Experiment in Bayesian Decision Problems -- Reducibility of Experiments in Multistep Decision Problems -- Concluding Remarks.
  note: by V. I. Ivanenko.
  subject:
    topic: Mathematics
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Business mathematics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Game theory
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Applications of Mathematics
  subject:
    topic: Business Mathematics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Game Theory, Economics, Social and Behav. Sciences
  subject:
    topic: Operation Research/Decision Theory
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781441955487
  identifier: http://dx.doi.org/10.1007/978-1-4419-5548-7
  record info:
    record creation date: 100528
    record change date: 20151204162314.0
    record identifier: 978-1-4419-5548-7