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Uncertainty in artificial intelligence 4

Author: Ross D Shachter
Publisher: Amsterdam ; New York : North-Holland ; New York, N.Y., U.S.A. : Distributors for the U.S. and Canada, Elsevier Science Pub. Co., 1990.
Series: Machine intelligence and pattern recognition, v. 9.
Edition/Format:   Print book : EnglishView all editions and formats
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Document Type: Book
All Authors / Contributors: Ross D Shachter
ISBN: 0444886508 9780444886507 0444887377 9780444887375
OCLC Number: 21600481
Description: xii, 422 pages : illustrations ; 24 cm.
Contents: I. Causal Models. On the Logic of Causal Models (D. Geiger, J. Pearl). Process, Structure, and Modularity in Reasoning with Uncertainty (B. D'Ambrosio). Probabilistic Causal Reasoning (T. Dean, K. Kanazawa). Generating Decision Structures and Causal Explanations for Decision Making (S. Star). Control of Problem Solving: Principles and Architecture (J.S. Breese, M.R. Fehling). Causal Networks: Semantics and Expressiveness (T. Verma, J. Pearl). II. Uncertainty Calculi and Comparisons. 1. Uncertainty Calculi. Stochastic Sensitivity Analysis Using Fuzzy Influence Diagrams (P. Jain, A.M. Agogino). A Linear Approximation Method for Probabilistic Inference (R.D. Shachter). Minimum Cross Entropy Reasoning in Recursive Causal Networks (W.X. Wen). Probabilistic Semantics and Defaults (E. Neufeld, D. Poole, R. Aleliunas). Modal Logics of Higher-Order Probability (P. Haddawy, A.M. Frisch). A General Non-Probabilistic Theory of Inductive Reasoning (W. Spohn). Epistemological Relevance and Statistical Knowledge (H.E. Kyburg, Jr.). Axioms for Probability and Belief-Function Propagation (P.F. Shenoy, G. Shafer). A Summary of a New Normative Theory of Probabilistic Logic (R. Aleliunas). Hierarchical Evidence and Belief Functions (P.K. Black, K.B. Laskey). On Probability Distributions over Possible Worlds (F. Bacchus). A Framework of Fuzzy Evidential Reasoning (J. Yen). 2. Comparisons. Parallel Belief Revision (D. Hunter). Evidential Reasoning Compared in a Network Usage Prediction Testbed: Preliminary Report (R.P. Loui). A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis (J. Kalagnanam, M. Henrion). An Empirical Comparison of Three Inference Methods (D. Heckerman). Modeling Uncertain and Vague Knowledge in Possibility and Evidence Theories (D. Dubois, H. Prade). Probabilistic Inference and Non-Monotonic Inference (H.E. Kyburg, Jr.). Multiple Decision Trees (S.W. Kwok, C. Carter). III. Knowledge Acquisition and Explanation. KNET: Integrating Hypermedia and Normative Bayesian Modeling (R.M. Chavez, G.F. Cooper). Generating Explanations of Decision Models Based on an Augmented Representation of Uncertainty (H.B. Jimison). IV. Applications. Induction and Uncertainty Management Techniques Applied to Veterinary Medical Diagnosis (M. Cecile, M. McLeish, P. Pascoe, W. Taylor). Predicting the Likely Behaviors of Continuous Nonlinear Systems in Equilibrium (A. Yeh). The Structure of Bayes Networks for Visual Recognition (J.M. Agosta). Utility-Based Control for Computer Vision (T.S. Levitt, T.O. Binford, G.J. Ettinger).
Series Title: Machine intelligence and pattern recognition, v. 9.
Other Titles: Uncertainty in artificial intelligence four
Responsibility: edited by Ross D. Shachter [and others].

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