Uncertainty in Artificial Intelligence
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Proceedings of the Third Conference Conference on Uncertainty in Artificial Intelligence ( 1987 )
Jul 10-12 1987, Seattle, WA

Edited By:
John Lemmer, Tod Levitt, Laveen Kanal
Published By: AUAI Press, Corvallis, Oregon
ISBN: 

A Heuristic Bayesian Approach to Knowledge Acquisition: Application to Analysis of Tissue-Type Plasminogen Activator
Ross Shachter , David Eddy , Vic Hasselblad , Robert Wolpert
A Knowledge Engineer's Comparison of Three Evidence Aggregation Methods
Donald Mitchell , Steven Harp , David Simkin
A Measure-Free Approach to Conditioning
I. Goodman
A Perspective on Confidence and Its Use in Focusing Attention During Knowledge Acquisition
David Heckerman , Holly Jimison
A Study of Associative Evidential Reasoning
Yizong Cheng , Rangasami Kashyap
Advantages and a Limitation of Using LEG Nets in a Real-TIme Problem
Thomas Slack
An Algorithm for Computing Probabilistic Propositions
Gregory Cooper
An Interesting Uncertainty-Based Combinatoric Problem in Spare Parts Forecasting: The FRED System
John Bacon
Automated Generation of Connectionist Expert Systems for Problems Involving Noise and Redundancy
Stephen Gallant
Bayesian Inference in Model-Based Machine Vision
Thomas Binford , Tod Levitt , Wallace Mann
Bayesian Prediction for Artificial Intelligence
Matthew Self , Peter Cheeseman
Belief in Belief Functions: An Examination of Shafer's Canonical Examples
Kathryn Laskey
Can Evidence Be Combined in the Dempster-Shafer Theory
John Yen
Coefficients of Relations for Probabilistic Reasoning
Silvio Ursic
Combining Symbolic and Numeric Approaches to Uncertainty Management
Bruce D'Ambrosio
Comparisons of Reasoning Mechanisms for Computer Vision
Ze-Nian Li
Compiling Fuzzy Logic Control Rules to Hardware Implementations
Stephen Chiu , Masaki Togai
Convergent Deduction for Probabilistic Logic
Peter Haddawy , Alan Frisch
Decision Tree Induction Systems: A Bayesian Analysis
Wray Buntine
Dempster-Shafer vs. Probabilistic Logic
Daniel Hunter
Do We Need Higher-Order Probabilities and, If So, What Do They Mean?
Judea Pearl
Efficient Inference on Generalized Fault Diagrams
Ross Shachter , Leonard Bertrand
Estimation Procedures for Robust Sensor Control
Greg Hager , Max Mintz
Evidential Reasoning in Image Understanding
Minchuan Zhang , Su-shing Chen
Explanation of Probabilistic Inference for Decision Support Systems
Christopher Elsaesser
Higher Order Probabilities
Henry Kyburg Jr.
Implementing a Bayesian Scheme for Revising Belief Commitments
Lashon Booker , Naveen Hota , Gavin Hemphill
Implementing Evidential Reasoning in Expert Systems
John Yen
Integrating Logical and Probabilistic Reasoning for Decision Making
John Breese , Edison Tse
Is Shafer General Bayes?
Paul Black
Modifiable Combining Functions
Paul Cohen , Glenn Shafer , Prakash Shenoy
NAIVE: A Method for Representing Uncertainty and Temporal Relationships in an Automated Reasoner
Michael Higgins
Nilsson's Probabilistic Entailment Extended to Dempster-Shafer Theory (Abstract Only)
Mary McLeish
Objective Probability
Henry Kyburg Jr.
Practical Issues in Constructing a Bayes' Belief Network
Max Henrion
Problem Structure and Evidential Reasoning
Richard Tong , Lee Appelbaum
Reasoning About Beliefs and Actions Under Computational Resource Constraints
Eric Horvitz
Satisfaction of Assumptions is a Weak Predictor of Performance
Ben Wise
Steps Towards Programs that Manage Uncertainty
Paul Cohen
Stochastic Simulation of Bayesian Belief Networks
Homer Chin , Gregory Cooper
Structuring Causal Tree Models with Continuous Variables
Lei Xu , Judea Pearl
Temporal Reasoning About Uncertain Worlds
Steve Hanks
The Automatic Training of Rule Bases that Use Numerical Uncertainty Representations
Richard Caruana
The Inductive Logic of Information Systems
Norman Dalkey
The Recovery of Causal Poly-Trees from Statistical Data
George Rebane , Judea Pearl
The Role of Calculi in Uncertain Inference Systems
Michael Wellman , David Heckerman
The Role of Tuning Uncertain Inference Systems
Ben Wise , Bruce Perrin , David Vaughan , Robert Yadrick
Theory-Based Inductive Learning: An Integration of Symbolic and Quantitative Methods
Spencer Star
Towards Solving the Multiple Extension Problem: Combining Defaults and Probabilities
Eric Neufeld , David Poole
Using T-Norm Based Uncertainty Calculi in a Naval Situation Assessment Application
Piero Bonissone
Using the Dempster-Shafer Scheme in a Diagnostic Expert System Shell
Gautam Biswas , Teywansh Anand

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