Conditional Objects and the Modeling of Uncertainties
Abstract
This reprint proposes a qualitative approach to conditioning which can be used in the modeling of uncertainties, as for example, in the combination of evidence problems that arise in probabilistic or Artificial Intelligence contexts. The resulting measure-free conditional objects are shown to be both compatible with, and to establish, new insights in the structure of ordinary conditional probabilities. In addition, explicit relations are developed between conditional objects and the often mistakenly equated standard logical implication operators. Extensions to other conditional entities, including fuzzy sets, are also outlined, as a special case of the main thesis of the paper: that conditioning in any context can be identified as simply the inverse of the transform representing conjunction. Keywords: Game theory. (kr)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1988
- Accession Number
- ADA209625
Entities
People
- I. R. Goodman