Description

Book Synopsis
Based on the proceedings of a conference on Influence Diagrams for Decision Analysis, Inference and Prediction held at the University of California at Berkeley in May of 1988, this is the first book devoted to the subject. The editors have brought together recent results from researchers actively investigating influence diagrams and also from practitioners who have used influence diagrams in developing models for problem-solving in a wide range of fields.

Table of Contents
Partial table of contents:

MODEL FORMULATION AND ANALYSIS.

From Influence to Relevance to Knowledge (R. Howard).

Complexity, Calibration and Causality in Influence Diagrams (T.Speed).

THEORETICAL FOUNDATIONS.

Statistical Principles on Graphs (J. Smith).

Influence and Belief Adjustment (M. Goldstein).

PROBLEMS AND APPLICATIONS: INDUSTRIAL.

Real Time Influence Diagrams for Monitoring and ControllingMechanical Systems (A. Agonino & K. Ramamurthi).

A Socio-technical Approach to Assessing Human Reliability (L.Phillips, et al.).

Bayesian Updating of Event Tree Parameters to Predict High RiskIncidents (R. Oliver & H. Yang).

PROBLEMS AND APPLICATIONS: MEDICAL.

EFFICIENCY AND COMPUTATIONAL ISSUES.

Towards Efficient Probabilistic Diagnosis in Multiply ConnectedBelief Networks (M. Henrion).

Towards Better Assessment and Sensitivity Procedures (R.Korsan).

Summary Observations (R. Howard).

Glossary.

Index.

Influence Diagrams Belief Nets and Decision Analysis

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    A Hardback by RM Oliver, James Q. Smith


      View other formats and editions of Influence Diagrams Belief Nets and Decision Analysis by RM Oliver

      Publisher: Wiley
      Publication Date: 31/01/1990
      ISBN13: 9780471923817, 978-0471923817
      ISBN10:

      Description

      Book Synopsis
      Based on the proceedings of a conference on Influence Diagrams for Decision Analysis, Inference and Prediction held at the University of California at Berkeley in May of 1988, this is the first book devoted to the subject. The editors have brought together recent results from researchers actively investigating influence diagrams and also from practitioners who have used influence diagrams in developing models for problem-solving in a wide range of fields.

      Table of Contents
      Partial table of contents:

      MODEL FORMULATION AND ANALYSIS.

      From Influence to Relevance to Knowledge (R. Howard).

      Complexity, Calibration and Causality in Influence Diagrams (T.Speed).

      THEORETICAL FOUNDATIONS.

      Statistical Principles on Graphs (J. Smith).

      Influence and Belief Adjustment (M. Goldstein).

      PROBLEMS AND APPLICATIONS: INDUSTRIAL.

      Real Time Influence Diagrams for Monitoring and ControllingMechanical Systems (A. Agonino & K. Ramamurthi).

      A Socio-technical Approach to Assessing Human Reliability (L.Phillips, et al.).

      Bayesian Updating of Event Tree Parameters to Predict High RiskIncidents (R. Oliver & H. Yang).

      PROBLEMS AND APPLICATIONS: MEDICAL.

      EFFICIENCY AND COMPUTATIONAL ISSUES.

      Towards Efficient Probabilistic Diagnosis in Multiply ConnectedBelief Networks (M. Henrion).

      Towards Better Assessment and Sensitivity Procedures (R.Korsan).

      Summary Observations (R. Howard).

      Glossary.

      Index.

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