Sciweavers

UAI
1993
13 years 5 months ago
Jeffrey's rule of conditioning generalized to belief functions
: Jeffrey’s rule of conditioning has been proposed in order to revise a probability measure by another probability function. We generalize it within the framework of the models b...
Philippe Smets
UAI
1993
13 years 5 months ago
On reasoning in networks with qualitative uncertainty
In this paper some initialwork towards a new approach to qualitative reasoning under uncertainty is presented. This method is not only applicable to qualitative probabilistic reas...
Simon Parsons, E. H. Mamdani
UAI
1993
13 years 5 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus
UAI
1993
13 years 5 months ago
Utility-Based Abstraction and Categorization
Based Abstraction and Categorization Eric J. Horvitz∗ and Adrian C. Klein Palo Alto Laboratory Rockwell International Science Center 444 High Street Palo Alto, CA 94301 We take ...
Eric Horvitz, Adrian Klein
UAI
1993
13 years 5 months ago
Probabilistic Assumption-Based Reasoning
In this paper the classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then the whole model is placed into the framework of...
Jürg Kohlas, Paul-André Monney
UAI
1993
13 years 5 months ago
Diagnosis of Multiple Faults: A Sensitivity Analysis
We compare the diagnostic accuracy of three diagnostic inference models: the simple Bayes model, the multimembership Bayes model, which is isomorphic to the parallel combination f...
David Heckerman, Michael Shwe
UAI
1993
13 years 5 months ago
Causal Independence for Knowledge Acquisition and Inference
I introduce a temporal belief-network representation of causal independence that a knowledge engineer can use to elicit probabilistic models. Like the current, atemporal belief-ne...
David Heckerman
UAI
1993
13 years 5 months ago
Inference Algorithms for Similarity Networks
We examine two types of similarity networks each based on a distinct notion of relevance. For both types of similarity networks we present an efficient inference algorithm that wo...
Dan Geiger, David Heckerman