Playing for Real is a problem-based textbook on game theory that has been widely used at both the undergraduate and graduate levels. The Coursepack Edition contains only the material necessary for a course of ten two-hour lectures plus problem classes. It comes with a disc of teaching aids including the author's own lecture presentations and two series of weekly exercise sets with answers.
Playing for Real is a problem-based textbook on game theory that has been widely used at both the undergraduate and graduate levels. The Coursepack Edition contains only the material necessary for a course of ten two-hour lectures plus problem classes. It comes with a disc of teaching aids including the author's own lecture presentations and two series of weekly exercise sets with answers.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Ken Binmore is a mathematician-turned-economist who has devoted his life to the theory of games and its applications in economics, evolutionary biology, psychology, and moral philosophy. He is well known for his part in designing the telecom auction that raised $35 billion for the British taxpayer, but his major research contributions are to the theory of bargaining and its testing in the laboratory. He is a Fellow of the British Academy and of the American Academy of Arts and Sciences. He is the author of 12 books and some 90 research papers. He is Emeritus Professor of Economics at University College London.
Inhaltsangabe
* Lecture 1: Getting Locked In * In this introductory lecture, a famous game called the Prisoners' Dilemma is * introduced and used to illustrate how game theory can be used to clarify a * variety of strategic problems. The idea of a Nash equilibrium makes its first * appearance. * Lecture 2: Backing Up * This chapter starts to explain how one can specify the rules of a game by * introducing the idea of a game tree. We learn how some games can be solved * by backward induction. * Lecture 3: Taking Chances * Chance moves are introduced. Bayes rule for updating conditional probabilities * appears for the first time. * Lecture 4: Accounting for Tastes * We learn that a rational player in a risky situation will behave as though maximizing * the expected value of a Von Neumann and Morgenstern utility function. * Lecture 5: Planning Ahead * The ideas of an extensive and strategic form of a game are consolidated. We * learn the mechanics of successively deleting dominated strategies. * Lecture 6: Mixing Things Up * Rational players will sometimes need to randomoize their strategy choice to * keep their opponents guessing. This chapter explains how to work with such * mixed strategies. * Lecture 7: Buying Cheap and Selling Dear * This chapter is an introduction to the use of game theory in economics. Students * of economics will find most topics are treated from a different angle than * they have probably seem before. * Lecture 8: Repeating Yourself * Most of the games we play in real life are repeated over and over again. This * makes a big difference to how they get played. * Lecture 9: Getting Together * This chapter applies game theory to bargaining. * Lecture 10: Knowing What to Believe * One of the big successes of game theory lies in its ability to handle some * situations in which players have good reason to conceal information from each * other. * Lecture 11: Taking Charge * This lecture is an optional extra about auctions and mechanism design. It can * serve as a possible substitute for Lecture 8 or 9.
* Lecture 1: Getting Locked In * In this introductory lecture, a famous game called the Prisoners' Dilemma is * introduced and used to illustrate how game theory can be used to clarify a * variety of strategic problems. The idea of a Nash equilibrium makes its first * appearance. * Lecture 2: Backing Up * This chapter starts to explain how one can specify the rules of a game by * introducing the idea of a game tree. We learn how some games can be solved * by backward induction. * Lecture 3: Taking Chances * Chance moves are introduced. Bayes rule for updating conditional probabilities * appears for the first time. * Lecture 4: Accounting for Tastes * We learn that a rational player in a risky situation will behave as though maximizing * the expected value of a Von Neumann and Morgenstern utility function. * Lecture 5: Planning Ahead * The ideas of an extensive and strategic form of a game are consolidated. We * learn the mechanics of successively deleting dominated strategies. * Lecture 6: Mixing Things Up * Rational players will sometimes need to randomoize their strategy choice to * keep their opponents guessing. This chapter explains how to work with such * mixed strategies. * Lecture 7: Buying Cheap and Selling Dear * This chapter is an introduction to the use of game theory in economics. Students * of economics will find most topics are treated from a different angle than * they have probably seem before. * Lecture 8: Repeating Yourself * Most of the games we play in real life are repeated over and over again. This * makes a big difference to how they get played. * Lecture 9: Getting Together * This chapter applies game theory to bargaining. * Lecture 10: Knowing What to Believe * One of the big successes of game theory lies in its ability to handle some * situations in which players have good reason to conceal information from each * other. * Lecture 11: Taking Charge * This lecture is an optional extra about auctions and mechanism design. It can * serve as a possible substitute for Lecture 8 or 9.
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