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: Uncertainty and Vagueness in Knowledge Based Systems
    sub title: Numerical Methods
  name:
    name part: Kruse, Rudolf.
    role:
      role term: creator
  name:
    name part: Schwecke, Erhard.
  name:
    name part: Heinsohn, Jochen.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: gw
    date issued: 1991
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (xi, 491 pages 59 illustrations)
  abstract: The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. Particular emphasis is put on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. The scope of the book also includes implementational aspects and a valuation of existing models and systems. The fundamental claim of the book is that vagueness and uncertainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms shows that efficiency requirements do not necessarily require renunciation of an uncompromising mathematical modeling approach. The results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets, and belief functions. The book is self-contained and addresses researchers and practitioners in the field of knowledge based sys- tems and decision support systems. It is suitable as a textbook for graduate-level students in AI, operations research, and applied probability.
  note: by Rudolf Kruse, Erhard Schwecke, Jochen Heinsohn.
  note: Electronic resource.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: System theory
  subject:
    topic: Mathematical optimization
  subject:
    topic: Distribution (Probability theory)
  subject:
    topic: Statistics
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Artificial Intelligence
  identifier: 9783642767029 (electronic bk.)
  identifier: 3642767028 (electronic bk.)
  identifier: 9783642767043
  identifier: 3642767044
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: AU@
    record creation date: 121227
    record change date: 20260422172150.8
    record identifier: in00003575113
    language of cataloging:
      language term: eng