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AAAI 1990

A Hybrid Framework for Representing Uncertain Knowledge

Conference Paper Representation and Uncertainty Artificial Intelligence

Abstract

This paper addresses the problem of bridging the gap between the fields of Knowledge Renresentation OCR) and Uncertain Reasoning (UR). The prohosed solution consists of a framework for representing uncertain knowledge in which two components, one dealing with (categorical) knowledge and one dealing with uncertainty about this knowledge, are singled out. In this sense, the framework is “hybrid”. This framework is characterized in both modeltheoretic and proof-theoretic terms. State of belief is represented by “belief sets”, defined in terms of the “functional approach to knowledge representation” suggested by Levesque. Examples are given, using first order logic and (a minimal subset of) M-Krypton for the KR side, and a yes/no trivial case and Dempster-Shafer theory for the UR side.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
165387246962929391