ML Anthology

Knowledge Integration for Conditional Probability Assessments

Angelo Gilio, Fulvio Spezzaferri
UAI 1992 pp. 98-103
doi:10.1016/B978-1-4832-8287-9.50018-9 /uai/1992/gilio1992uai-knowledge/

Abstract

In the probabilistic approach to uncertainty management the input knowledge is usually represented by means of some probability distributions. In this paper we assume that the input knowledge is given by two discrete conditional probability distributions, represented by two stochastic matrices P and Q. The consistency of the knowledge base is analyzed. Coherence conditions and explicit formulas for the extension to marginal distributions are obtained in some special cases.

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Text

Gilio and Spezzaferri. "Knowledge Integration for Conditional Probability Assessments." Conference on Uncertainty in Artificial Intelligence, 1992. doi:10.1016/B978-1-4832-8287-9.50018-9

Markdown

[Gilio and Spezzaferri. "Knowledge Integration for Conditional Probability Assessments." Conference on Uncertainty in Artificial Intelligence, 1992.](https://mlanthology.org/uai/1992/gilio1992uai-knowledge/) doi:10.1016/B978-1-4832-8287-9.50018-9

BibTeX

@inproceedings{gilio1992uai-knowledge,
  title     = {{Knowledge Integration for Conditional Probability Assessments}},
  author    = {Gilio, Angelo and Spezzaferri, Fulvio},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1992},
  pages     = {98-103},
  doi       = {10.1016/B978-1-4832-8287-9.50018-9},
  url       = {https://mlanthology.org/uai/1992/gilio1992uai-knowledge/}
}