English

Towards Precision of Probabilistic Bounds Propagation

Artificial Intelligence 2013-03-25 v1

Abstract

The DUCK-calculus presented here is a recent approach to cope with probabilistic uncertainty in a sound and efficient way. Uncertain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally. The basic inference mechanism relies on local bounds propagation, implementable by deductive databases with a bottom-up fixpoint evaluation. In situations, where no precise bounds are deducible, it can be combined with simple operations research techniques on a local scope. In particular, we provide new precise analytical bounds for probabilistic entailment.

Keywords

Cite

@article{arxiv.1303.5434,
  title  = {Towards Precision of Probabilistic Bounds Propagation},
  author = {Helmut Thone and Ulrich Guntzer and Werner Kiessling},
  journal= {arXiv preprint arXiv:1303.5434},
  year   = {2013}
}

Comments

Appears in Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence (UAI1992)

R2 v1 2026-06-21T23:46:12.803Z