Accession Number : ADA262789


Title :   On Modeling of If-Then Rules for Probabilistic Inference


Descriptive Note : Professional paper


Corporate Author : NAVAL COMMAND CONTROL AND OCEAN SURVEILLANCE CENTER RDT AND E DIV SAN DIEGO CA


Personal Author(s) : Goodman, I R ; Nguyen, Hung T


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a262789.pdf


Report Date : Feb 1993


Pagination or Media Count : 13


Abstract : We identify various situations in probabilistic intelligent systems in which conditionals (rules) as mathematical entities as well as their conditional logic operations are needed. In discussing Bayesian updating procedure and belief function construction, we provide a new method for modeling if...then rules as Boolean elements, and yet, compatible with conditional probability quantifications.


Descriptors :   *MATHEMATICAL MODELS , *STATISTICAL INFERENCE , RANDOM VARIABLES , PROBABILITY , BAYES THEOREM , BOOLEAN ALGEBRA


Subject Categories : Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE