Risk Assessment and Decision Analysis with Bayesian Networks

K10450

RISK

ASSESSMENT

AND

DECISION

ANALYSIS

WITH

BAYESIAN

NETWORKS

RISK ASSESSMENT AND DECISION ANALYSIS

WITH BAYESIAN NETWORKS

RISK ASSESSMENT AND DECISION ANALYSIS

WITH BAYESIAN NETWORKS

NORMAN FENTON

MARTIN NEIL

FENTON • NEIL

Although many Bayesian Network (BN) applications are now in everyday use,

BNs have not yet achieved mainstream penetration. Focusing on practical real-

world problem solving and model building, as opposed to algorithms and theory,

Risk Assessment and Decision Analysis with Bayesian Networks explains

how to incorporate knowledge with data to develop and use (Bayesian) causal

models of risk that provide powerful insights and better decision making.

• Provides all tools necessary to build and run realistic Bayesian network

models

• Supplies extensive example models based on real risk assessment

problems in a wide range of application domains provided; for example,

nance, safety, systems reliability, law, and more

• Introduces all necessary mathematics, probability, and statistics as

needed

The book rst establishes the basics of probability, risk, and building and

using BN models, then goes into the detailed applications. The underlying BN

algorithms appear in appendices rather than the main text since there is no

need to understand them to build and use BN models. Keeping the body of

the text free of intimidating mathematics, the book provides pragmatic advice

about model building to ensure models are built efciently.

A dedicated website, www.BayesianRisk.com, contains executable versions

of all the models described, exercises and worked solutions for all chapters,

PowerPoint slides, numerous other resources, and a free downloadable copy

of the AgenaRisk software.

Mathematics

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