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Lack of information – average distribution of probability density

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Języki publikacji
EN
Abstrakty
EN
In many real problems we have to face up to information gaps. The paper presents the method of decreasing granulation of elementary events, which finds an average distribution of probability density, which represents infinite number of distributions. If we know the range of the unknown value and have qualitative knowledge about the general character of its distribution, then we can use this knowledge to surmount the information gap in a better way than the way proposed by the principle of indifference. According to the authors' knowledge the concept of the safe distribution is new and unknown in the literature. It is of fundamental importance for probability theory.
Rocznik
Strony
173--182
Opis fizyczny
Bibliogr. 7 poz., rys., tab.
Twórcy
autor
  • Faculty of Computer Science and Information Technology, Szczecin University of Technology
autor
  • Faculty of Computer Science and Information Technology, Szczecin University of Technology
  • Quantitative Methods Institute, Szczecin Maritime University
Bibliografia
  • [1] Bandrit C., Dubois D., Guyonenet D. Joint propagation and exploitation of probabilistic and possibilistic information in risk assessment. IEEE Transactions on Fuzzy Systems, Vol. 14, No. 5, pp. 593-608, 2006.
  • [2] Wikipedia, The Free Encyclopedia, http://en.wikipedia.org/wiki/Principle_of-indifference, 2008.
  • [3] Magidor O. The classical theory of probability and the principle of indifference. 5th Annual Carnegie Mellon/University of Pittsburgh Graduate Philosophy Conference, http:// www.andrew.cmu/org/conference/2003, pp.1-17, 2003.
  • [4] Piegat A., Landowski M. Surmounting information gaps - safe distributions of probability density. Methods of Applied Computer Science, No. 2/2007, pp. 113-126, Szczecin, 2007 [in Polish]
  • [5] Russel R., Norwig P. Artificial Intelligence – A Modern Approach. Second edition, Prentice Hall, Upper Saddle River, NJ, 2003.
  • [6] Rutkowski L. Metody i techniki sztucznej inteligencji. Wydawnictwo Naukowe PWN, Warszawa, 2005.
  • [7] Yakov B. H. Info-gap decision theory-decisions under severe uncertainty. Second edition, Academic Press, London, 2006.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-64e20e12-5f4b-44d4-80b4-d0a5f47741e2
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