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Probability Theory

  • Rudolf Kruse
  • Erhard Schwecke
  • Jochen Heinsohn
Part of the Artificial Intelligence book series (AI)

Abstract

In this chapter we present probability theory as the basic tool for handling uncertainty, i.e. partial beliefs. In order to obtain a mathematically sound representation we always keep in mind a “relative frequency” interpretation or alternatively a degree of confirmation of probabilities. The main shortcoming of many textbooks is that the treatment of imprecise probabilities, which is important for obtaining suitable knowledge representation facilities, is left out. Our approach to this problem relies on the consideration of classes of probabilities.

Keywords

Sample Space Subjective Probability Probability Interval Maximum Entropy Principle Ship Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Rudolf Kruse
    • 1
  • Erhard Schwecke
    • 1
  • Jochen Heinsohn
    • 2
  1. 1.Department of Computer ScienceTechnical University of BraunschweigBraunschweigGermany
  2. 2.German Research Center for Artificial Intelligence (DFKI)Saarbrücken 11Germany

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