| Description |
1 online resource (vi, 542 pages) : illustrations |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Front Cover; Uncertainty inArtificialIntelligence; Copyright Page; Table of Contents; Preface; Acknowledgements; Part 1: Foundations; Chapter 1. Causality in Bayesian Belief Networks; Abstract; 1 INTRODUCTION; 2 SIMULTANEOUS EQUATIONS MODELS; 3 CAUSALITY IN BAYESIAN BELIEF NETWORKS; 4 CONCLUSION; Acknowledgments; References; Chapter 2. From Conditional Oughts to Qualitative Decision Theory; Abstract; 1 INTRODUCTION; 2 INFINITESIMALPROBABILITIES, RANKINGFUNCTIONS, CAUSALNETWORKS, AND ACTIONS; 3 SUMMARY OF RESULTS; 4 FROM UTILITIES AND BELIEFS TO GOALS AND ACTIONS. |
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5 COMBINING ACTIONS AND OBSERVATIONS6 RELATIONS TO OTHER ACCOUNTS; 7 CONCLUSION; Acknowledgements; References; Part 2: Applications and Empirical Comparisons; Chapter 3. A Probabilistic Algorithm for Calculating Structure:Borrowing from Simulated Annealing; Abstract; 1 MOLECULAR STRUCTURE; 2 THE DATA REPRESENTATION; 3 EXPERIMENTS PERFORMED; 4 RESULTS; 5 DISCUSSION; 6 CONCLUSIONS; Acknowledgements; References; Chapter 4. A Study of Scaling Issues in Bayesian Belief Networks for Ship Classification; Abstract; 1 Introduction; 2 Overview; 3 Network Structure; 4 Integration of Belief Values. |
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5 Discussion6 Conclusion; References; CHAPTER 5. TRADEOFFS IN CONSTRUCTING AND EVALUATING TEMPORAL INFLUENCE DIAGRAMS; Abstract; 1 INTRODUCTION; 2 TEMPORAL BAYESIAN NETWORKS; 3 TID CONSTRUCTION FROM KNOWLEDGE BASES; 4 DOMAIN-SPECIFIC TIME-SERIES MODELS; 5 MODEL SELECTION APPROACHES; 6 EVALUATING TRADEOFFS; 7 RELATED LITERATURE; 8 CONCLUSIONS; Acknowledgements; References; Chapter 6. End-User Construction of Influence Diagrams for Bayesian Statistics; Abstract; 1 INTRODUCTION; 2 STATISTICAL MODEL; 3 SEMANTIC INTERFACE: THE PATIENT-FLOW DIAGRAM. |
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4 METADATA-STATE DIAGRAM: THE COHORT-STATE DIAGRAM5 CONSTRUCTION STEPS; 6 IMPLEMENTATION; 7 OTHER WORK; 8 CONCLUSION; Acknowledgments; References; Chapter 7. On Considering Uncertainty and Alternatives in Low-Level Vision; Abstract; 1 INTRODUCTION; 2 REGIONS, SEGMENTS, AND SEGMENTATIONS; 3 SEGMENT-LEVEL UNCERTAINTY; 4 SEGMENTATION-LEVEL UNCERTAINTY; 5 REGION-LEVEL UNCERTAINTY; 6 OBTAINING PRIORS; 7 ALGORITHMS; 8 AN EXPERIMENTAL EXAMPLE; 9 CONCLUSION; Acknowledgement; References; Chapter 8. Forecasting Sleep Apnea with Dynamic Network Models; Abstract; 1 INTRODUCTION; 2 RELATED WORK. |
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3 THE DYNAMIC NETWORK MODEL4 THE DYNEMO IMPLEMENTATION; 5 THE SLEEP-APNEA FORECASTING PROBLEM; 6 CONCLUSIONS; Acknowledgments; References; Chapter 9. Normative Engineering Risk Management Systems; Abstract; 1 INTRODUCTION; 2 ENGINEERING RISK MANAGEMENT SYSTEMS; 3 ADVANCED RISK MANAGEMENT SYSTEM PROJECT; 4 NORMATIVE SYSTEM OVERVIEW; 5 NORMATIVE SYSTEM ACTIVITIES; 6 RESEARCH ISSUES; 7 CONCLUSIONS; Acknowledgements; References; Chapter 10. Diagnosis of Multiple Faults: A Sensitivity Analysis; Abstract; 1 INTRODUCTION; 2 THE MODELS; 3 EXPERIMENTAL DESIGN; 4 RESULTS AND DISCUSSION. |
| Summary |
Uncertainty in Artificial Intelligence. |
| Subject |
Artificial intelligence -- Congresses.
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Uncertainty (Information theory) -- Congresses.
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Intelligence artificielle -- Congrès. |
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Incertitude (Théorie de l'information) -- Congrès. |
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Artificial intelligence |
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Uncertainty (Information theory) |
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Kongress |
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Künstliche Intelligenz |
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Unvollkommene Information |
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Intelligence artificielle -- Congrès. |
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Incertitude (théorie de l'information) -- Congrès. |
| Genre |
Congress |
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proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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Washington (DC, 1993)
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| Added Author |
Heckerman, David E., editor.
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Mamdani, Abe, editor.
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Conference on Uncertainity in Artificial Intelligence (9th : 1993 : Catholic University of America)
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| Other Form: |
Print version: Uncertainty in artificial intelligence 1558603069 (OCoLC)29265800 |
| ISBN |
9781483214511 (electronic bk.) |
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1483214516 (electronic bk.) |
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