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A Survey of Belief Revision and Updating Rules in Various Uncertainty Models*.
- Source :
- International Journal of Intelligent Systems; Jan1994, Vol. 9 Issue 1, p61-100, 40p
- Publication Year :
- 1994
-
Abstract
- The paper proposes a parallel survey of revision and updating operations available in the probability theory and in the possibility theory frameworks. In these two formalisms the current state of knowledge is generally represented by a [0,l]-avalued function whose domain is art exhaustive set of mutually exclusive possible states of the world. However, in possibility theory, IS unit-interval can be viewed as a purely ordinal scale. Two general kinds of operations can be defined on this assignment function: conditioning, and imaging (or "projection"). The difference between these two operations is analogous to the one made between belief revision à la Gärdenfors and updating à la Kaisuno rid Mendelzon in the logical framework. In the probabilistic framework these two operations are respectively Bayesian conditioning and Lewis' imaging. Counterparts to these operations are presented for the ponibilistic framework including the cue of conditioning upon uncertain observations, and justifications we given which parallel the ones existing for the probabilistic operations. More particularly, it is recalled that pouibilistic conditioning satisfies all the postulates proposed by Alchounón, Gärdenfors and Makinson for belief revision (stated in possibilistic terms), and it is proved that possibilistic imaging satisfies all the postulates proposed by Katsuno and Mendelzon. The situation where our current knowledge is stated in terms of weighted logical propositions is discussed in connection to possibility theory. Revision in other more complex numerical furmalisms, namely belief and plausibility functions, and upper and lower probabilities is also surveyed. Recent results on the revision of conditional knowledge bases are also reviewed. The frameworks of belief functions, upper and lower probabilities and conditional bases we more sophisticated than the previous ones because they enable to distinguish between factual evidence and generic knowledge in a cognitive state. This framework leads to two forms of belief revision respectively taking care of the revision of evidence and the revision of knowledge. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08848173
- Volume :
- 9
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- International Journal of Intelligent Systems
- Publication Type :
- Academic Journal
- Accession number :
- 14085424
- Full Text :
- https://doi.org/10.1002/int.4550090105