Vorobyev, Oleg (2009): Eventology versus contemporary theories of uncertainty. Published in: XII International EM'2009 Conference, Program and Abstracts (20. February 2009): pp. 1331.

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Abstract
The development of probability theory together with the Bayesian approach in the three last centuries is caused by two factors: the variability of the physical phenomena and partial ignorance about them. As now it is standard to believe [Dubois, 2007], the nature of these key factors is so various, that their descriptions are required special uncertainty theories, which differ from the probability theory and the Bayesian credo, and provide a better account of the various facets of uncertainty by putting together probabilistic and setvalued representations of information to catch a distinction between variability and ignorance. Eventology [Vorobyev, 2007], a new direction of probability theory and philosophy, offers the original event approach to the description of variability and ignorance, entering an agent, together with his/her beliefs, directly in the frameworks of scientific research in the form of eventological distribution of his/her own events. This allows eventology, by putting together probabilistic and setevent representation of information and philosophical concept of event as cobeing [Bakhtin, 1920], to provide a unified strong account of various aspects of uncertainty catching distinction between variability and ignorance and opening an opportunity to define imprecise probability as a probability of imprecise event in the mathematical frameworks of Kolmogorov's probability theory [Kolmogorov, 1933].
Item Type:  MPRA Paper 

Original Title:  Eventology versus contemporary theories of uncertainty 
English Title:  Eventology versus contemporary theories of uncertainty 
Language:  English 
Keywords:  uncertainty, probability, event, cobeing, eventology, imprecise event 
Subjects:  C  Mathematical and Quantitative Methods > C0  General > C02  Mathematical Methods C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General 
Item ID:  13961 
Depositing User:  Oleg Vorobyev 
Date Deposited:  12. Mar 2009 07:40 
Last Modified:  12. Feb 2013 18:15 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/13961 