ML Anthology

A Model for Non-Monotonic Reasoning Using Dempster's Rule

Mary McLeish
UAI 1990 pp. 481-494
/uai/1990/mcleish1990uai-model/

Abstract

Considerable attention has been given to the problem of non-monotonic reasoning in a belief function framework. Earlier work (M. Ginsberg) proposed solutions introducing meta-rules which recognized conditional independencies in a probabilistic sense. More recently an e-calculus formulation of default reasoning (J. Pearl) shows that the application of Dempster's rule to a non-monotonic situation produces erroneous results. This paper presents a new belief function interpretation of the problem which combines the rules in a way which is more compatible with probabilistic results and respects conditions of independence necessary for the application of Dempster's combination rule. A new general framework for combining conflicting evidence is also proposed in which the normalization factor becomes modified. This produces more intuitively acceptable results.

PDF Semantic Scholar

Cite

Text

McLeish. "A Model for Non-Monotonic Reasoning Using Dempster's Rule." Conference on Uncertainty in Artificial Intelligence, 1990.

Markdown

[McLeish. "A Model for Non-Monotonic Reasoning Using Dempster's Rule." Conference on Uncertainty in Artificial Intelligence, 1990.](https://mlanthology.org/uai/1990/mcleish1990uai-model/)

BibTeX

@inproceedings{mcleish1990uai-model,
  title     = {{A Model for Non-Monotonic Reasoning Using Dempster's Rule}},
  author    = {McLeish, Mary},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1990},
  pages     = {481-494},
  url       = {https://mlanthology.org/uai/1990/mcleish1990uai-model/}
}