Abstract
Bayes’ rule is the basis of probabilistic reasoning. It enables to surmount information gaps. However, it requires the knowledge of prior distributions of probabilistic variables. If this distribution is not known then, according to the principle of indifference, the uniform distribution has to be assumed. The uniform distribution is frequently and heavily criticized. The paper presents a safe distribution of probability density that can be often used instead of the uniform distribution to surmount information gaps. According to the authors’ knowledge the concept of the safe distribution is new and unknown in the literature.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kneale, W.: Probability and induction. Oxford University Press, Oxford (1952)
Magidor, O.: The classical theory of probability and the principle of indifference. In: 5th Annual Carnegie Mellon/University of Pittsburgh Graduate Philosophy Conference, pp. 1–17 (2003), http://www.andrew.cmu.edu/org/conference/2003
Russel, R., Norvig, P.: Artificial Intelligence - A Modern Approach, 2nd edn. Prentice Hall, Upper Saddle River (2003)
Yakov, B.H.: Info-gap decision theory-decisions under severe uncertainty, 2nd edn. Academic Press, London (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Piegat, A., Landowski, M. (2008). Bayes’ Rule, Principle of Indifference, and Safe Distribution. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_64
Download citation
DOI: https://doi.org/10.1007/978-3-540-69731-2_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
Online ISBN: 978-3-540-69731-2
eBook Packages: Computer ScienceComputer Science (R0)