William P Fox
Decision Analysis through Modeling and Game Theory
William P Fox
Decision Analysis through Modeling and Game Theory
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This unique book presents decision analysis in the context of mathematical modeling and game theory. The author emphasizes and focuses on the model formulation and modeling building skills required for decision analysis, as well as the technology to support the analysis.
This unique book presents decision analysis in the context of mathematical modeling and game theory. The author emphasizes and focuses on the model formulation and modeling building skills required for decision analysis, as well as the technology to support the analysis.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 296
- Erscheinungstermin: 8. November 2024
- Englisch
- Abmessung: 234mm x 156mm x 17mm
- Gewicht: 445g
- ISBN-13: 9781032726915
- ISBN-10: 1032726911
- Artikelnr.: 70680899
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 296
- Erscheinungstermin: 8. November 2024
- Englisch
- Abmessung: 234mm x 156mm x 17mm
- Gewicht: 445g
- ISBN-13: 9781032726915
- ISBN-10: 1032726911
- Artikelnr.: 70680899
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
Dr. William P. Fox is currently a visiting professor of Computational Operations Research at the College of William and Mary. He is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School and teaches a three-course sequence in mathematical modeling for decision making. He received his Ph.D. in Industrial Engineering from Clemson University. He has taught at the United States Military Academy for twelve years until retiring and at Francis Marion University where he was the chair of mathematics for eight years. He has many publications and scholarly activities including twenty plus books and one hundred and fifty journal articles. Books by William P. Fox from CRC Press: Probability and Statistics for Engineering and the Sciences with Modeling using R (w/Rodney X. Sturdivant, 2023, CRC Press Mathematical Modeling in the Age of the Pandemic, 2021, CRC Press. Advanced Problem Solving Using Maple: Applied Mathematics, Operations Research, Business Analytics, and Decision Analysis (w/William Bauldry), 2020, CRC Press. Mathematical Modeling with Excel (w/Brian Albright), 2020, CRC Press. Nonlinear Optimization: Models and Applications, 2020, CRC Press. Advanced Problem Solving with Maple: A First Course (w/William Bauldry), 2019. CRC Press. Mathematical Modeling for Business Analytics, 2018, CRC Press.
Chapter 1: Introduction to Decision Models
1.1 Overview of Decision Making
1.2 Decision Theory
1.3 Game Theory: Total Conflict
Example 1.5: A Total Conflict Game with Pure Strategies
1.4 Game Theory: Partial Conflict
1.5 Mathematical Modeling of Decisions
1.4 ILLUSTRATE EXAMPLES
1.5 Technology
Summary
Chapter 2 Decision Theory and Expected Value
2.1 Introduction
2.2 Expected Value
2.3 Decisions Under Risk: Probabilities are known or estimated in advance
2.4 Decisions under Uncertainty: Probabilities are not known nor can they
be estimated
2.5 Decision Trees
2.6 Sequential Decisions and Conditional Probability (from Fox,
Mathematical Modeling for Business Analytics, Taylor and Francis, 2018)
Chapter 3 Decisions under certainty: Mathematical Programming Modeling:
Linear, Integer, and Mixed Integer Optimization
3.1 Introduction
3.2 Formulating Linear Programming Problems
3.3 Graphical Linear Programming
3.4 Linear Programming with Technology
3.5 Case Studies in Linear Programming
Projects
3.5.1 Modeling of Ranking Units using Data Envelopment Analysis (DEA) as a
LP
3.5.2 Recruiting Raleigh Office (modified from McGrath, 2007)
Exercises
References and Suggested Further Readings
Chapter 4 Multi-Attribute Decision Making using weighting schemes with SAW,
AHP and TOPSIS
4.1 Weighting Methods
4.1.1 Rank Order Centroid (ROC)
4.1.2 Ratio Method for Weights
4.1.3 Pairwise Comparison (AHP)
4.1.4 Entropy Method:
4.2 Simple Additive Weights (SAW) Method
4.3 Weighted Product Method
4.4 Analytical Hierarchy Process
4.5 Technique of Order Preference by Similarity to the Ideal Solution
Methodology
Normalization
Additional Reading and References
EXERCISES Chapter 4
CHAPTER 5 Game Theory: Total Conflict
5.1 Introduction to Total Conflict Games
5.2 Models with Pure Strategy Solutions
5.2.1 Movement Arrows with two players and a payoff matrix:
5.2.2 Saddle Point Method
5.3 Dominance and Dominated strategies
Exercises Section 5.1 Pure Strategy Games
5.3 Mixed Strategy in two player 2 strategy games
5.3 Linear Programming and Total Conflict Games
Summary
Chapter 6 Partial Conflict Games: The Classical Two-Player Games. Error!
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6.1 Partial Conflict Simultaneous Games Introduction
6.2 The Prisoner's Dilemma
6.3 The Game of Chicken
Reference and Further Readings
Chapter 7 Utility Theory
7.1 Introduction
7.2 Ordinal Numbers
7.3 Cardinal numbers
7.4 Utility
7.4 Von Neumann-Morgenstern Utilities Applied to Game Theory.
7.5 An alternative approach to the lottery method in utility theory for
game theory
7.5.1 Lottery Method Illustrated
7.5.2 AHP Method
7.5.3 AHP Example in Game Theory
7.6 Summary and Conclusions
References
Chapter 8. Nash Equilibrium and Non-Cooperative Solutions in Partial
Conflict Games
8.1 Introduction
8.2 Pure Strategies and Dominance review in symmetric games
8.3 Equalizing Strategies
8.4 Prudential Strategies with LP
8.5 Applications
EXERCISES
Chapter 9 Evolutionary stable Strategies
9.1 Introduction
Summary
Exercises Chapter 9
Reference
Chapter 10 Communications
10.1 Introduction
10.2 The Game of Chicken Without Communication
10.3 The Game of Chicken With Communication
10.3.1 Moving First or Committing to Move First
10.3.2 Issuing a Threat
10.3.3 Issuing a Promise
10.4 Credibility
Classical Game Theory and the Missile Crisis (from Brahm ,1994)
Theory of Moves and the Missile Crisis
Chapter 10 Exercises
References and Further Reading
Chapter 11 Nash Arbitration Method
11.1 Introduction to Nash Arbitration
11.2 Methods without calculus
11.3 More than two strategies
11.4 Writer's Guild Strike example with cardinal numbers
Introduction
Nash Arbitration Scheme
Chapter 12 Three Person Games
12.1 Three Person Zero-Sum games
12.2 Three-Person Partial Conflict Game ( Non-Zero Sum Game).
12.4 NON-ZERO Sum (non-constant sum) with no pure strategies.
12.5 3-Person game with Technology
Exercises
Chapter 13 Extensive Form Games
13.1 Introduction
Example 1. Kidnapping for ransom
Applying TOM
Exercises Chapter 13
1.1 Overview of Decision Making
1.2 Decision Theory
1.3 Game Theory: Total Conflict
Example 1.5: A Total Conflict Game with Pure Strategies
1.4 Game Theory: Partial Conflict
1.5 Mathematical Modeling of Decisions
1.4 ILLUSTRATE EXAMPLES
1.5 Technology
Summary
Chapter 2 Decision Theory and Expected Value
2.1 Introduction
2.2 Expected Value
2.3 Decisions Under Risk: Probabilities are known or estimated in advance
2.4 Decisions under Uncertainty: Probabilities are not known nor can they
be estimated
2.5 Decision Trees
2.6 Sequential Decisions and Conditional Probability (from Fox,
Mathematical Modeling for Business Analytics, Taylor and Francis, 2018)
Chapter 3 Decisions under certainty: Mathematical Programming Modeling:
Linear, Integer, and Mixed Integer Optimization
3.1 Introduction
3.2 Formulating Linear Programming Problems
3.3 Graphical Linear Programming
3.4 Linear Programming with Technology
3.5 Case Studies in Linear Programming
Projects
3.5.1 Modeling of Ranking Units using Data Envelopment Analysis (DEA) as a
LP
3.5.2 Recruiting Raleigh Office (modified from McGrath, 2007)
Exercises
References and Suggested Further Readings
Chapter 4 Multi-Attribute Decision Making using weighting schemes with SAW,
AHP and TOPSIS
4.1 Weighting Methods
4.1.1 Rank Order Centroid (ROC)
4.1.2 Ratio Method for Weights
4.1.3 Pairwise Comparison (AHP)
4.1.4 Entropy Method:
4.2 Simple Additive Weights (SAW) Method
4.3 Weighted Product Method
4.4 Analytical Hierarchy Process
4.5 Technique of Order Preference by Similarity to the Ideal Solution
Methodology
Normalization
Additional Reading and References
EXERCISES Chapter 4
CHAPTER 5 Game Theory: Total Conflict
5.1 Introduction to Total Conflict Games
5.2 Models with Pure Strategy Solutions
5.2.1 Movement Arrows with two players and a payoff matrix:
5.2.2 Saddle Point Method
5.3 Dominance and Dominated strategies
Exercises Section 5.1 Pure Strategy Games
5.3 Mixed Strategy in two player 2 strategy games
5.3 Linear Programming and Total Conflict Games
Summary
Chapter 6 Partial Conflict Games: The Classical Two-Player Games. Error!
Bookmark not defined.
6.1 Partial Conflict Simultaneous Games Introduction
6.2 The Prisoner's Dilemma
6.3 The Game of Chicken
Reference and Further Readings
Chapter 7 Utility Theory
7.1 Introduction
7.2 Ordinal Numbers
7.3 Cardinal numbers
7.4 Utility
7.4 Von Neumann-Morgenstern Utilities Applied to Game Theory.
7.5 An alternative approach to the lottery method in utility theory for
game theory
7.5.1 Lottery Method Illustrated
7.5.2 AHP Method
7.5.3 AHP Example in Game Theory
7.6 Summary and Conclusions
References
Chapter 8. Nash Equilibrium and Non-Cooperative Solutions in Partial
Conflict Games
8.1 Introduction
8.2 Pure Strategies and Dominance review in symmetric games
8.3 Equalizing Strategies
8.4 Prudential Strategies with LP
8.5 Applications
EXERCISES
Chapter 9 Evolutionary stable Strategies
9.1 Introduction
Summary
Exercises Chapter 9
Reference
Chapter 10 Communications
10.1 Introduction
10.2 The Game of Chicken Without Communication
10.3 The Game of Chicken With Communication
10.3.1 Moving First or Committing to Move First
10.3.2 Issuing a Threat
10.3.3 Issuing a Promise
10.4 Credibility
Classical Game Theory and the Missile Crisis (from Brahm ,1994)
Theory of Moves and the Missile Crisis
Chapter 10 Exercises
References and Further Reading
Chapter 11 Nash Arbitration Method
11.1 Introduction to Nash Arbitration
11.2 Methods without calculus
11.3 More than two strategies
11.4 Writer's Guild Strike example with cardinal numbers
Introduction
Nash Arbitration Scheme
Chapter 12 Three Person Games
12.1 Three Person Zero-Sum games
12.2 Three-Person Partial Conflict Game ( Non-Zero Sum Game).
12.4 NON-ZERO Sum (non-constant sum) with no pure strategies.
12.5 3-Person game with Technology
Exercises
Chapter 13 Extensive Form Games
13.1 Introduction
Example 1. Kidnapping for ransom
Applying TOM
Exercises Chapter 13
Chapter 1: Introduction to Decision Models
1.1 Overview of Decision Making
1.2 Decision Theory
1.3 Game Theory: Total Conflict
Example 1.5: A Total Conflict Game with Pure Strategies
1.4 Game Theory: Partial Conflict
1.5 Mathematical Modeling of Decisions
1.4 ILLUSTRATE EXAMPLES
1.5 Technology
Summary
Chapter 2 Decision Theory and Expected Value
2.1 Introduction
2.2 Expected Value
2.3 Decisions Under Risk: Probabilities are known or estimated in advance
2.4 Decisions under Uncertainty: Probabilities are not known nor can they
be estimated
2.5 Decision Trees
2.6 Sequential Decisions and Conditional Probability (from Fox,
Mathematical Modeling for Business Analytics, Taylor and Francis, 2018)
Chapter 3 Decisions under certainty: Mathematical Programming Modeling:
Linear, Integer, and Mixed Integer Optimization
3.1 Introduction
3.2 Formulating Linear Programming Problems
3.3 Graphical Linear Programming
3.4 Linear Programming with Technology
3.5 Case Studies in Linear Programming
Projects
3.5.1 Modeling of Ranking Units using Data Envelopment Analysis (DEA) as a
LP
3.5.2 Recruiting Raleigh Office (modified from McGrath, 2007)
Exercises
References and Suggested Further Readings
Chapter 4 Multi-Attribute Decision Making using weighting schemes with SAW,
AHP and TOPSIS
4.1 Weighting Methods
4.1.1 Rank Order Centroid (ROC)
4.1.2 Ratio Method for Weights
4.1.3 Pairwise Comparison (AHP)
4.1.4 Entropy Method:
4.2 Simple Additive Weights (SAW) Method
4.3 Weighted Product Method
4.4 Analytical Hierarchy Process
4.5 Technique of Order Preference by Similarity to the Ideal Solution
Methodology
Normalization
Additional Reading and References
EXERCISES Chapter 4
CHAPTER 5 Game Theory: Total Conflict
5.1 Introduction to Total Conflict Games
5.2 Models with Pure Strategy Solutions
5.2.1 Movement Arrows with two players and a payoff matrix:
5.2.2 Saddle Point Method
5.3 Dominance and Dominated strategies
Exercises Section 5.1 Pure Strategy Games
5.3 Mixed Strategy in two player 2 strategy games
5.3 Linear Programming and Total Conflict Games
Summary
Chapter 6 Partial Conflict Games: The Classical Two-Player Games. Error!
Bookmark not defined.
6.1 Partial Conflict Simultaneous Games Introduction
6.2 The Prisoner's Dilemma
6.3 The Game of Chicken
Reference and Further Readings
Chapter 7 Utility Theory
7.1 Introduction
7.2 Ordinal Numbers
7.3 Cardinal numbers
7.4 Utility
7.4 Von Neumann-Morgenstern Utilities Applied to Game Theory.
7.5 An alternative approach to the lottery method in utility theory for
game theory
7.5.1 Lottery Method Illustrated
7.5.2 AHP Method
7.5.3 AHP Example in Game Theory
7.6 Summary and Conclusions
References
Chapter 8. Nash Equilibrium and Non-Cooperative Solutions in Partial
Conflict Games
8.1 Introduction
8.2 Pure Strategies and Dominance review in symmetric games
8.3 Equalizing Strategies
8.4 Prudential Strategies with LP
8.5 Applications
EXERCISES
Chapter 9 Evolutionary stable Strategies
9.1 Introduction
Summary
Exercises Chapter 9
Reference
Chapter 10 Communications
10.1 Introduction
10.2 The Game of Chicken Without Communication
10.3 The Game of Chicken With Communication
10.3.1 Moving First or Committing to Move First
10.3.2 Issuing a Threat
10.3.3 Issuing a Promise
10.4 Credibility
Classical Game Theory and the Missile Crisis (from Brahm ,1994)
Theory of Moves and the Missile Crisis
Chapter 10 Exercises
References and Further Reading
Chapter 11 Nash Arbitration Method
11.1 Introduction to Nash Arbitration
11.2 Methods without calculus
11.3 More than two strategies
11.4 Writer's Guild Strike example with cardinal numbers
Introduction
Nash Arbitration Scheme
Chapter 12 Three Person Games
12.1 Three Person Zero-Sum games
12.2 Three-Person Partial Conflict Game ( Non-Zero Sum Game).
12.4 NON-ZERO Sum (non-constant sum) with no pure strategies.
12.5 3-Person game with Technology
Exercises
Chapter 13 Extensive Form Games
13.1 Introduction
Example 1. Kidnapping for ransom
Applying TOM
Exercises Chapter 13
1.1 Overview of Decision Making
1.2 Decision Theory
1.3 Game Theory: Total Conflict
Example 1.5: A Total Conflict Game with Pure Strategies
1.4 Game Theory: Partial Conflict
1.5 Mathematical Modeling of Decisions
1.4 ILLUSTRATE EXAMPLES
1.5 Technology
Summary
Chapter 2 Decision Theory and Expected Value
2.1 Introduction
2.2 Expected Value
2.3 Decisions Under Risk: Probabilities are known or estimated in advance
2.4 Decisions under Uncertainty: Probabilities are not known nor can they
be estimated
2.5 Decision Trees
2.6 Sequential Decisions and Conditional Probability (from Fox,
Mathematical Modeling for Business Analytics, Taylor and Francis, 2018)
Chapter 3 Decisions under certainty: Mathematical Programming Modeling:
Linear, Integer, and Mixed Integer Optimization
3.1 Introduction
3.2 Formulating Linear Programming Problems
3.3 Graphical Linear Programming
3.4 Linear Programming with Technology
3.5 Case Studies in Linear Programming
Projects
3.5.1 Modeling of Ranking Units using Data Envelopment Analysis (DEA) as a
LP
3.5.2 Recruiting Raleigh Office (modified from McGrath, 2007)
Exercises
References and Suggested Further Readings
Chapter 4 Multi-Attribute Decision Making using weighting schemes with SAW,
AHP and TOPSIS
4.1 Weighting Methods
4.1.1 Rank Order Centroid (ROC)
4.1.2 Ratio Method for Weights
4.1.3 Pairwise Comparison (AHP)
4.1.4 Entropy Method:
4.2 Simple Additive Weights (SAW) Method
4.3 Weighted Product Method
4.4 Analytical Hierarchy Process
4.5 Technique of Order Preference by Similarity to the Ideal Solution
Methodology
Normalization
Additional Reading and References
EXERCISES Chapter 4
CHAPTER 5 Game Theory: Total Conflict
5.1 Introduction to Total Conflict Games
5.2 Models with Pure Strategy Solutions
5.2.1 Movement Arrows with two players and a payoff matrix:
5.2.2 Saddle Point Method
5.3 Dominance and Dominated strategies
Exercises Section 5.1 Pure Strategy Games
5.3 Mixed Strategy in two player 2 strategy games
5.3 Linear Programming and Total Conflict Games
Summary
Chapter 6 Partial Conflict Games: The Classical Two-Player Games. Error!
Bookmark not defined.
6.1 Partial Conflict Simultaneous Games Introduction
6.2 The Prisoner's Dilemma
6.3 The Game of Chicken
Reference and Further Readings
Chapter 7 Utility Theory
7.1 Introduction
7.2 Ordinal Numbers
7.3 Cardinal numbers
7.4 Utility
7.4 Von Neumann-Morgenstern Utilities Applied to Game Theory.
7.5 An alternative approach to the lottery method in utility theory for
game theory
7.5.1 Lottery Method Illustrated
7.5.2 AHP Method
7.5.3 AHP Example in Game Theory
7.6 Summary and Conclusions
References
Chapter 8. Nash Equilibrium and Non-Cooperative Solutions in Partial
Conflict Games
8.1 Introduction
8.2 Pure Strategies and Dominance review in symmetric games
8.3 Equalizing Strategies
8.4 Prudential Strategies with LP
8.5 Applications
EXERCISES
Chapter 9 Evolutionary stable Strategies
9.1 Introduction
Summary
Exercises Chapter 9
Reference
Chapter 10 Communications
10.1 Introduction
10.2 The Game of Chicken Without Communication
10.3 The Game of Chicken With Communication
10.3.1 Moving First or Committing to Move First
10.3.2 Issuing a Threat
10.3.3 Issuing a Promise
10.4 Credibility
Classical Game Theory and the Missile Crisis (from Brahm ,1994)
Theory of Moves and the Missile Crisis
Chapter 10 Exercises
References and Further Reading
Chapter 11 Nash Arbitration Method
11.1 Introduction to Nash Arbitration
11.2 Methods without calculus
11.3 More than two strategies
11.4 Writer's Guild Strike example with cardinal numbers
Introduction
Nash Arbitration Scheme
Chapter 12 Three Person Games
12.1 Three Person Zero-Sum games
12.2 Three-Person Partial Conflict Game ( Non-Zero Sum Game).
12.4 NON-ZERO Sum (non-constant sum) with no pure strategies.
12.5 3-Person game with Technology
Exercises
Chapter 13 Extensive Form Games
13.1 Introduction
Example 1. Kidnapping for ransom
Applying TOM
Exercises Chapter 13