Finding a Posterior Domain Probability Distribution by Specifying Nonspecific Evidence

Details Finding a Posterior Domain Probability Distribution by Specifying Nonspecific Evidence Finding a Posterior Domain Probability Distribution by Specifying Nonspecific Evidence

2003-05-16

arxiv.org/abs/cs/0305015v1

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 3(2) (1995) 163-185

Computer Science

Artificial Intelligence

23 pages, 1 figure

Scientific paper

This article is an extension of the results of two earlier articles. In [J. Schubert, On nonspecific evidence, Int. J. Intell. Syst. 8 (1993) 711-725] we established within Dempster-Shafer theory a criterion function called the metaconflict function. With this criterion we can partition into subsets a set of several pieces of evidence with propositions that are weakly specified in the sense that it may be uncertain to which event a proposition is referring. In a second article [J. Schubert, Specifying nonspecific evidence, in Cluster-based specification techniques in Dempster-Shafer theory for an evidential intelligence analysis of multiple target tracks, Ph.D. Thesis, TRITA-NA-9410, Royal Institute of Technology, Stockholm, 1994, ISBN 91-7170-801-4] we not only found the most plausible subset for each piece of evidence, we also found the plausibility for every subset that this piece of evidence belongs to the subset. In this article we aim to find a posterior probability distribution regarding the number of subsets. We use the idea that each piece of evidence in a subset supports the existence of that subset to the degree that this piece of evidence supports anything at all. From this we can derive a bpa that is concerned with the question of how many subsets we have. That bpa can then be combined with a given prior domain probability distribution in order to obtain the sought-after posterior domain distribution.

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