English

Rules, Belief Functions and Default Logic

Artificial Intelligence 2013-04-05 v1

Abstract

This paper describes a natural framework for rules, based on belief functions, which includes a repre- sentation of numerical rules, default rules and rules allowing and rules not allowing contraposition. In particular it justifies the use of the Dempster-Shafer Theory for representing a particular class of rules, Belief calculated being a lower probability given certain independence assumptions on an underlying space. It shows how a belief function framework can be generalised to other logics, including a general Monte-Carlo algorithm for calculating belief, and how a version of Reiter's Default Logic can be seen as a limiting case of a belief function formalism.

Keywords

Cite

@article{arxiv.1304.1134,
  title  = {Rules, Belief Functions and Default Logic},
  author = {Nic Wilson},
  journal= {arXiv preprint arXiv:1304.1134},
  year   = {2013}
}

Comments

Appears in Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence (UAI1990)

R2 v1 2026-06-21T23:53:25.941Z