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arxiv: 1304.1134 · v1 · pith:POVADQJNnew · submitted 2013-03-27 · 💻 cs.AI

Rules, Belief Functions and Default Logic

classification 💻 cs.AI
keywords rulesbeliefdefaultallowingframeworkfunctionfunctionslogic
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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.

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