English

Reasoning about Uncertainty in Metric Spaces

Artificial Intelligence 2012-07-02 v1

Abstract

We set up a model for reasoning about metric spaces with belief theoretic measures. The uncertainty in these spaces stems from both probability and metric. To represent both aspect of uncertainty, we choose an expected distance function as a measure of uncertainty. A formal logical system is constructed for the reasoning about expected distance. Soundness and completeness are shown for this logic. For reasoning on product metric space with uncertainty, a new metric is defined and shown to have good properties.

Keywords

Cite

@article{arxiv.1206.6856,
  title  = {Reasoning about Uncertainty in Metric Spaces},
  author = {Seunghwan Lee},
  journal= {arXiv preprint arXiv:1206.6856},
  year   = {2012}
}

Comments

Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)

R2 v1 2026-06-21T21:27:47.741Z