【决策分析，国际版】Foundations of Decision Analysis, Global Edition

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Foundations of Decision Analysis, Global Edition

Ali E. Abbas, University of Southern California
Ronald A. Howard, Stanford University



ISBN 9781292079691
ISBN 10 129207969X
Published 19/03/2015
Published by Pearson Higher Ed USA
Pages 832

For courses in Decision Making and Engineering.

The Fundamentals of Analyzing and Making Decisions

Foundations of Decision Analysis is a groundbreaking text that explores the art of decision making, both in life and in professional settings. By exploring themes such as dealing with uncertainty and understanding the distinction between a decision and its outcome, the First Edition teaches students to achieve clarity of action in any situation.

The book treats decision making as an evolutionary process from a scientific standpoint. Strategic decision-making analysis is presented as a tool to help students understand, discuss, and settle on important life choices. Through this text, students will understand the specific thought process that occurs behind approaching any decision to make easier and better life choices for themselves.

Table of contents

Part 1 Defining a Good Decision
Chapter 1: Introduction to Quality Decision Making
Chapter 2: Experiencing a Decision

Part 2 Clear Thinking and Characterization
Chapter 3: Clarifying Values
Chapter 4: Precise Decision Language
Chapter 5: Possibilities
Chapter 6: Handling Uncertainty
Chapter 7: Relevance

Part 3 Making any Decision
Chapter 8: Rules of Actional Thought
Chapter 9: The Party Problem
Chapter 10: Using a Value Measure

Part 4 Building on the Rules
Chapter 11: Risk Attitude
Chapter 12: Sensitivity Analysis
Chapter 13: Basic Information Gathering
Chapter 14: Decision Diagrams

Part 5 Characterizing What you Know
Chapter 15: Encoding a Probability Distribution on a Measure
Chapter 16: From Phenomenon to Assessment

Part 6 Framing a Decision
Chapter 17: Framing a Decision

Part 7 Advanced Information Gathering
Chapter 18: Valuing Information from Multiple Sources
Chapter 19: Options
Chapter 20: Detectors with Multiple Indications
Chapter 21: Decisions with Influences

Part 8 Characterizing What You Want
Chapter 22: The Logarithmic u-Curve
Chapter 23: The Linear Risk Tolerance u-Curve
Chapter 24: Approximate Expressions for the Certain
Chapter 25: Deterministic and Probabilistic Dominance
Chapter 26: Decisions with Multiple Attributes (1)–Ordering
Chapter 27: Decisions with Multiple Attributes (2)–Value Functions
Chapter 28: Decisions with Multiple Attributes (3)–Preference Equivalent
Prospects with Preference and Value Functions
for Investment Cash Flows: Time Preference
Probabilities Over Value

Part 9 Some Practical Extensions
Chapter 29: Betting on Disparate Belief
Chapter 30: Learning from Experimentation
Chapter 31: Auctions and Bidding
Chapter 32: Evaluating, Scaling, and Sharing Uncertain Deals
Chapter 33: Making Risky Decisions
Chapter 34: Decisions with a High Probability of Death

Part 10 Computing Decision Problems
Chapter 35: Discretizing Continuous Probability Distributions
Chapter 36: Solving Decision Problems by Simulation

Part 11 Professional Decisions
Chapter 37: The Decision Analysis Cycle
Chapter 38: Topics in Organizational Decision Making
Chapter 39: Coordinating the Decision Making of Large

Part 12 Ethical Considerations
Chapter 40: Decisions and Ethics Groups

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