Efnisyfirlit

• GAME THEORY
• Title
• Copyright
• Contents
• Preface
• PART I Rational Decision Making
  • Chapter 1 The Single-Person Decision Problem
    • 1.1 Actions, Outcomes, and Preferences
      • 1.1.1 Preference Relations
      • 1.1.2 Payoff Functions
    • 1.2 The Rational Choice Paradigm
    • 1.4 Exercises
    • 1.3 Summary
  • Chapter 2 Introducing Uncertainty and Time
    • 2.1 Risk, Nature, and Random Outcomes
      • 2.1.1 Finite Outcomes and Simple Lotteries
      • 2.1.2 Simple versus Compound Lotteries
      • 2.1.3 Lotteries over Continuous Outcomes
    • 2.2 Evaluating Random Outcomes
      • 2.2.1 Expected Payoff: The Finite Case
      • 2.2.2 Expected Payoff: The Continuous Case
      • 2.2.3 Caveat: It’s Not Just the Order Anymore
      • 2.2.4 Risk Attitudes
      • 2.2.5 The St. Petersburg Paradox
    • 2.3 Rational Decision Making with Uncertainty
      • 2.3.1 Rationality Revisited
      • 2.3.2 Maximizing Expected Payoffs
    • 2.4 Decisions over Time
      • 2.4.1 Backward Induction
      • 2.4.2 Discounting Future Payoffs
    • 2.5 Applications
      • 2.5.1 The Value of Information
      • 2.5.2 Discounted Future Consumption
    • 2.6 Theory versus Practice
    • 2.7 Summary
    • 2.8 Exercises
• PART II Static Games of Complete Information
  • Chapter 3 Preliminaries
    • 3.1 Normal-Form Games with Pure Strategies
      • 3.1.1 Example: The Prisoner’s Dilemma
      • 3.1.2 Example: Cournot Duopoly
      • 3.1.3 Example: Voting on a New Agenda
    • 3.2 Matrix Representation: Two-Player Finite Game
      • 3.2.1 Example: The Prisoner’s Dilemma
      • 3.2.2 Example: Rock-Paper-Scissors
    • 3.3 Solution Concepts
      • 3.3.1 Assumptions and Setup
      • 3.3.2 Evaluating Solution Concepts
    • 3.3.3 Evaluating Outcomes
    • 3.4 Summary
    • 3.5 Exercises
  • Chapter 4 Rationality and Common Knowledge
    • 4.1 Dominance in Pure Strategies
      • 4.1.1 Dominated Strategies
      • 4.1.2 Dominant Strategy Equilibrium
      • 4.1.3 Evaluating Dominant Strategy Equilibrium
    • 4.2 Iterated Elimination of Strictly Dominated Pure Strategies
      • 4.2.1 Iterated Elimination and Common Knowledge of Rationality
      • 4.2.2 Example: Cournot Duopoly
      • 4.2.3 Evaluating IESDS
    • 4.3 Beliefs, Best Response, and Rationalizability
      • 4.3.1 The Best Response
      • 4.3.2 Beliefs and Best-Response Correspondences
      • 4.3.3 Rationalizability
      • 4.3.4 The Cournot Duopoly Revisited
      • 4.3.5 The “p-Beauty Contest”
      • 4.3.6 Evaluating Rationalizability
    • 4.4 Summary
    • 4.5 Exercises
  • Chapter 5 Pinning Down Beliefs: Nash Equilibrium
    • 5.1 Nash Equilibrium in Pure Strategies
      • 5.1.1 Pure-Strategy Nash Equilibrium in a Matrix
      • 5.1.2 Evaluating the Nash Equilibria Solution
    • 5.2 Nash Equilibrium: Some Classic Applications
      • 5.2.1 Two Kinds of Societies
      • 5.2.2 The Tragedy of the Commons
      • 5.2.3 Cournot Duopoly
      • 5.2.4 Bertrand Duopoly
      • 5.2.5 Political Ideology and Electoral Competition
    • 5.3 Summary
    • 5.4 Exercises
  • Chapter 6 Mixed Strategies
    • 6.1 Strategies, Beliefs, and Expected Payoffs
      • 6.1.1 Finite Strategy Sets
      • 6.1.2 Continuous Strategy Sets
      • 6.1.3 Beliefs and Mixed Strategies
      • 6.1.4 Expected Payoffs
    • 6.2 Mixed-Strategy Nash Equilibrium
      • 6.2.1 Example: Matching Pennies
      • 6.2.2 Example: Rock-Paper-Scissors
      • 6.2.3 Multiple Equilibria: Pure and Mixed
    • 6.3 IESDS and Rationalizability Revisited
    • 6.4 Nash’s Existence Theorem
    • 6.5 Summary
    • 6.6 Exercises
• PART III Dynamic Games of Complete Information
  • Chapter 7 Preliminaries
    • 7.1 The Extensive-Form Game
      • 7.1.1 Game Trees
      • 7.1.2 Imperfect versus Perfect Information
    • 7.2 Strategies and Nash Equilibrium
      • 7.2.1 Pure Strategies
      • 7.2.2 Mixed versus Behavioral Strategies
      • 7.2.3 Normal-Form Representation of Extensive-Form Games
    • 7.3 Nash Equilibrium and Paths of Play
    • 7.4 Summary
    • 7.5 Exercises
  • Chapter 8 Credibility and Sequential Rationality
    • 8.1 Sequential Rationality and Backward Induction
    • 8.2 Subgame-Perfect Nash Equilibrium: Concept
    • 8.3 Subgame-Perfect Nash Equilibrium: Examples
      • 8.3.1 The Centipede Game
      • 8.3.2 Stackelberg Competition
      • 8.3.3 Mutually Assured Destruction
      • 8.3.4 Time-Inconsistent Preferences
    • 8.4 Summary
    • 8.5 Exercises
  • Chapter 9 Multistage Games
    • 9.1 Preliminaries
    • 9.2 Payoffs
    • 9.3 Strategies and Conditional Play
    • 9.4 Subgame-Perfect Equilibria
    • 9.5 The One-Stage Deviation Principle
    • 9.6 Summary
    • 9.7 Exercises
  • Chapter 10 Repeated Games
    • 10.1 Finitely Repeated Games
    • 10.2 Infinitely Repeated Games
      • 10.2.1 Payoffs
      • 10.2.2 Strategies
    • 10.3 Subgame-Perfect Equilibria
    • 10.4 Application: Tacit Collusion
    • 10.5 Sequential Interaction and Reputation
      • 10.5.1 Cooperation as Reputation
      • 10.5.2 Third-Party Institutions as Reputation Mechanisms
      • 10.5.3 Reputation Transfers without Third Parties
    • 10.6 The Folk Theorem: Almost Anything Goes
    • 10.7 Summary
    • 10.8 Exercises
  • Chapter 11 Strategic Bargaining
    • 11.1 One Round of Bargaining: The Ultimatum Game
    • 11.2 Finitely Many Rounds of Bargaining
    • 11.3 The Infinite-Horizon Game
    • 11.4 Application: Legislative Bargaining
      • 11.4.1 Closed-Rule Bargaining
      • 11.4.2 Open-Rule Bargaining
    • 11.5 Summary
    • 11.6 Exercises
• PART IV Static Games of Incomplete Information
  • Chapter 12 Bayesian Games
    • 12.1 Strategic Representation of Bayesian Games
      • 12.1.1 Players, Actions, Information, and Preferences
      • 12.1.2 Deriving Posteriors from a Common Prior: A Player’s Beliefs
      • 12.1.3 Strategies and Bayesian Nash Equilibrium
    • 12.2 Examples
      • 12.2.1 Teenagers and the Game of Chicken
      • 12.2.2 Study Groups
    • 12.3 Inefficient Trade and Adverse Selection
    • 12.4 Committee Voting
    • 12.5 Mixed Strategies Revisited: Harsanyi’s Interpretation
    • 12.6 Summary
    • 12.7 Exercises
  • Chapter 13 Auctions and Competitive Bidding
    • 13.1 Independent Private Values
      • 13.1.1 Second-Price Sealed-Bid Auctions
      • 13.1.2 English Auctions
      • 13.1.3 First-Price Sealed-Bid and Dutch Auctions
      • 13.1.4 Revenue Equivalence
    • 13.2 Common Values and the Winner’s Curse
    • 13.3 Summary
    • 13.4 Exercises
  • Chapter 14 Mechanism Design
    • 14.1 Setup: Mechanisms as Bayesian Games
      • 14.1.1 The Players
      • 14.1.2 The Mechanism Designer
      • 14.1.3 The Mechanism Game
    • 14.2 The Revelation Principle
    • 14.3 Dominant Strategies and Vickrey-Clarke-Groves Mechanisms
      • 14.3.1 Dominant Strategy Implementation
      • 14.3.2 Vickrey-Clarke-Groves Mechanisms
    • 14.4 Summary
    • 14.5 Exercises
• PART V Dynamic Games of Incomplete Information
  • Chapter 15 Sequential Rationality with Incomplete Information
    • 15.1 The Problem with Subgame Perfection
    • 15.2 Perfect Bayesian Equilibrium
    • 15.3 Sequential Equilibrium
    • 15.4 Summary
    • 15.5 Exercises
  • Chapter 16 Signaling Games
    • 16.1 Education Signaling: The MBA Game
    • 16.2 Limit Pricing and Entry Deterrence
      • 16.2.1 Separating Equilibria
      • 16.2.2 Pooling Equilibria
    • 16.3 Refinements of Perfect Bayesian Equilibrium in Signaling Games
    • 16.4 Summary
    • 16.5 Exercises
  • Chapter 17 Building a Reputation
    • 17.1 Cooperation in a Finitely Repeated Prisoner’s Dilemma
    • 17.2 Driving a Tough Bargain
    • 17.3 A Reputation for Being “Nice”
    • 17.4 Summary
    • 17.5 Exercises
  • Chapter 18 Information Transmission and Cheap Talk
    • 18.1 Information Transmission: A Finite Example
    • 18.2 Information Transmission: The Continuous Case
    • 18.3 Application: Information and Legislative Organization
    • 18.4 Summary
    • 18.5 Exercises
  • Chapter 19 Mathematical Appendix
    • 19.1 Sets and Sequences
      • 19.1.1 Basic Definitions
      • 19.1.2 Basic Set Operations
    • 19.2 Functions
      • 19.2.1 Basic Definitions
      • 19.2.2 Continuity
    • 19.3 Calculus and Optimization
      • 19.3.1 Basic Definitions
      • 19.3.2 Differentiation and Optimization
      • 19.3.3 Integration
    • 19.4 Probability and Random Variables
      • 19.4.1 Basic Definitions
      • 19.4.2 Cumulative Distribution and Density Functions
      • 19.4.3 Independence, Conditional Probability, and Bayes’ Rule
      • 19.4.4 Expected Values
• References
• Index

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