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ORCID1st UAI 1985: Los Angeles, CA, USA
- Laveen N. Kanal, John F. Lemmer:
UAI '85: Proceedings of the First Annual Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, USA, July 10-12, 1985. Elsevier 1988, ISBN 0-444-70058-7 - Raj Bhatnagar, Laveen N. Kanal:
Handling Uncertain Information: A Review of Numeric and Non-numeric Methods. 3-26 - Carlos Alberto Berenstein, Laveen N. Kanal:
Consensus Rules. 27-34 - B. Chandrasekaran, Michael C. Tanner:
Uncertainty Handling in Expert Systems: Uniform vs. Task-Specific Formalisms. 35-46 - David J. Spiegelhalter:
Probabilistic Reasoning in Predictive Expert Systems. 47-68 - Ben P. Wise, Max Henrion:
A Framework for Comparing Uncertain Inference Systems to Probability. 69-84 - Peter C. Cheeseman:
Probabilistic vs. Fuzzy Reasoning. 85-102 - Lotfi A. Zadeh:
Is Probability Theory Sufficient for Dealing with Uncertainty in AI: A Negative View. 103-116 - John F. Lemmer:
Confidence Factors, Empiricism and the Dempster-Shafer Theory of Evidence. 117-126 - Glenn Shafer:
Probability Judgment in Artificial Intelligence. 127-136 - Eric Horvitz, David Heckerman:
The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research. 137-152 - Benjamin N. Grosof:
Evidential Confirmation as Transformed Probability: On the Duality of Priors and Updates. 153-166 - David Heckerman:
Probabilistic Interpretation for MYCIN's Certainty Factors. 167-196 - Rodney W. Johnson:
Independence and Bayesian Updating Methods. 197-202 - Daniel Hunter:
Uncertain Reasoning Using Maximum Entropy Inference. 203-210 - John E. Shore:
Relative Entropy, Probabilistic Inference, and AI. 211-216 - Piero P. Bonissone, Keith Decker:
Selecting Uncertainty Calculi and Granularity: An Experiment in Trading-off Precision and Complexity. 217-248 - Alf C. Zimmer:
What Uncertainty Judgments Can Tell About the Underlying Subjective Probabilities. 249-258 - Benjamin N. Grosof:
An Inequality Paradigm for Probabilistic Knowledge: The Logic of Conditional Probability Intervals. 259-278 - Marvin S. Cohen:
An Expert System Framework for Non-monotonic Reasoning About Probabilistic Assumptions. 279-294 - Robert M. Fung, Chee Yee Chong:
Metaprobability and Dempster-Shafer in Evidential Reasoning. 295-302 - Gerald Liu:
Knowledge Structures and Evidential Reasoning in Decision Analysis. 303-316 - Ronald R. Yager:
A General Approach to Decision Making with Evidential Knowledge. 317-330 - Matthew L. Ginsberg:
Implementing Probabilistic Reasoning. 331-338 - Samuel Holtzman, John S. Breese:
Exact Reasoning About Uncertainty: On the Design of Expert Systems for Decision Support. 339-346 - Tod S. Levitt:
Model-Based Probabilistic Situation Inference in Hierarchical Hypothesis Spaces. 347-356 - Judea Pearl:
A Constraint-Propagation Approach to Probabilistic Reasoning. 357-370 - Ross D. Shachter:
Intelligent Probabilistic Inference. 371-382 - David S. Vaughan, Bruce M. Perrin, Robert M. Yadrick, Peter D. Holden, Karl G. Kempf:
An Odds Ratio Based Inference Engine. 383-392 - Norman C. Dalkey:
Inductive Inference and the Representation of Uncertainty. 393-398 - Henry Hamburger:
Representing, Combining and Using Uncertain Estimates. 399-414 - Stephen Jose Hanson, Malcolm Bauer:
Machine Learning, Clustering and Polymorphy. 415-428 - Larry A. Rendell:
Induction, of and by Probability. 429-446 - John Fox:
Three Arguments for Extending the Framework of Probability. 447-458 - Ronald Prescott Loui:
Interval-Based Decisions for Reasoning Systems. 459-472 - Ray J. Solomonoff:
The Application of Algorithmic Probability to Problems in Artificial Intelligence. 473-494 - Bruce Abramson:
An Explanation of and Cure for Minimax Pathology. 495-504 - Dana S. Nau, Paul Walton Purdom Jr., Chun-Hung Tzeng:
An Evaluation of Two Alternatives to Minimax. 505-509
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