Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition
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9780444700582

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Probabilistic Interpretations for Mycin's Certainty Factors* *This work was supported in part by the Josiah Macy, Jr. Foundation, the Henry J. Kaiser Family Foundation, and the Ford Aerospace Corporation. Computing facilities were provided by the SUMEX-AIM resource under NIH grant RR-00785.

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50017-6 ◽

1986 ◽

pp. 167-196 ◽

Cited By ~ 73

Author(s):

David Heckerman

Keyword(s):

Kaiser Family Foundation ◽

Aerospace Corporation

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Inductive Inference and the Representation of Uncertainty

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50034-6 ◽

1986 ◽

pp. 393-397 ◽

Cited By ~ 3

Author(s):

N.C. DALKEY

Keyword(s):

Inductive Inference

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Intelligent Probabilistic Inference

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50032-2 ◽

1986 ◽

pp. 371-382 ◽

Cited By ~ 19

Author(s):

Ross D. Shachter

Keyword(s):

Probabilistic Inference

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Induction, of and by Probability* *This work was supported in part by an operating grant from the Natural Sciences and Engineering Research Council of Canada.

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50037-1 ◽

1986 ◽

pp. 429-443 ◽

Cited By ~ 3

Author(s):

Larry Rendell

Keyword(s):

Research Council ◽

Natural Sciences ◽

Engineering Research

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A Constraint – Propagation Approach to Probabilistic Reasoning* *This work was supported in part by the National Science Foundation, Grant #DSR 83–13875

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50031-0 ◽

1986 ◽

pp. 357-369 ◽

Cited By ~ 39

Author(s):

Judea PEARL

Keyword(s):

National Science Foundation ◽

Probabilistic Reasoning ◽

Constraint Propagation ◽

National Science Foundation Grant ◽

National Science

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Independence and Bayesian Updating Methods* *Reprinted from the Artificial Intelligence Journal with permission of the publisher, North Holland, Amsterdam.

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50018-8 ◽

1986 ◽

pp. 197-201 ◽

Cited By ~ 6

Author(s):

Rodney W. Johnson

Keyword(s):

Artificial Intelligence ◽

Bayesian Updating

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Contributors

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50005-x ◽

1986 ◽

pp. vii-viii

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Copyright page

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50003-6 ◽

1986 ◽

pp. iv

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Front Matter

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50002-4 ◽

1986 ◽

pp. iii

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An Evaluation of Two Alternatives to Minimax

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-70058-2.50042-5 ◽

1986 ◽

pp. 505-509

Author(s):

Dana Nau ◽

Paul Purdom ◽

Chun-Hung Tzeng

Keyword(s):

Two Alternatives

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Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern RecognitionLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Elsevier

Probabilistic Interpretations for Mycin's Certainty Factors* *This work was supported in part by the Josiah Macy, Jr. Foundation, the Henry J. Kaiser Family Foundation, and the Ford Aerospace Corporation. Computing facilities were provided by the SUMEX-AIM resource under NIH grant RR-00785.

Inductive Inference and the Representation of Uncertainty

Intelligent Probabilistic Inference

Induction, of and by Probability* *This work was supported in part by an operating grant from the Natural Sciences and Engineering Research Council of Canada.

A Constraint – Propagation Approach to Probabilistic Reasoning* *This work was supported in part by the National Science Foundation, Grant #DSR 83–13875

Independence and Bayesian Updating Methods* *Reprinted from the Artificial Intelligence Journal with permission of the publisher, North Holland, Amsterdam.

Contributors

Copyright page

Front Matter

An Evaluation of Two Alternatives to Minimax

Uncertainty in Artificial Intelligence - Machine Intelligence and Pattern Recognition
Latest Publications