Essentials of Game Theory: A Concise, Multidisciplinary Introduction

Morgan & Claypool Publishers
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Game theory is the mathematical study of interaction among independent, self-interested agents. The audience for game theory has grown dramatically in recent years, and now spans disciplines as diverse as political science, biology, psychology, economics, linguistics, sociology, and computer science, among others. What has been missing is a relatively short introduction to the field covering the common basis that anyone with a professional interest in game theory is likely to require. Such a text would minimize notation, ruthlessly focus on essentials, and yet not sacrifice rigor. This Synthesis Lecture aims to fill this gap by providing a concise and accessible introduction to the field. It covers the main classes of games, their representations, and the main concepts used to analyze them. Table of Contents: Games in Normal Form / Analyzing Games: From Optimality to Equilibrium / Further Solution Concepts for Normal-Form Games / Games with Sequential Actions: The Perfect-information Extensive Form / Generalizing the Extensive Form: Imperfect-Information Games / Repeated and Stochastic Games / Uncertainty about Payoffs: Bayesian Games / Coalitional Game Theory / History and References / Index
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Additional Information

Publisher
Morgan & Claypool Publishers
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Published on
Dec 31, 2008
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Pages
88
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ISBN
9781598295931
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Language
English
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Genres
Computers / Intelligence (AI) & Semantics
Mathematics / Game Theory
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This content is DRM protected.
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A game is an efficient model of interactions between agents, for the following basic reason: the players follow fixed rules, have interests on all possible final outcomes of the game, and the final result for them does not depend only from the choices they individually make, but also from the choices of other agents. Thus the focus is actually on the fact that in a game there are several agents interacting. In fact, more recently this theory took the name of Interactive Decision Theory. It is related to classical decision theory, but it takes into account the presence of more than one agent taking decisions. As we shall constantly see, this radically changes the background and sometimes even the intuition behind classical decision theory. So, in few words, game theory is the study of taking optimal decisions in presence of multiple players (agents).


Thus a game is a simplified, yet very efficient, model of real life every day situa- tions. Though the first, and probably more intuitive, applications of the theory were in an economical setting, theoretical models and tools of this theory nowadays are spread on various disciplines. To quote some of them, we can start from psychology: a more modern approach than classical psychanalysis takes into account that the hu- man being is mainly an interactive agent. So to speak, we play everyday with our professors/students, with our parents/children, with our lover, when bargaining with somebody. Also the Law and the Social Sciences are obviously interested in Game Theory, since the rules play a crucial role in inducing the behaviour of the agents. Not many years after the first systematic studies in Game Theory, interesting ap- plications appeared to animals, starting with the analysis of competing species. It is much more recent and probably a little surprising to know that recent applications of the theory deal with genes in microbiology, or computers in telecommunication problems. In some sense, today many scholars do believe that these will be the more interesting applications in the future: for reasons that we shall constantly see later, humans in some sense are not so close to the rational player imagined by the theory, while animals and computers “act” in a more rational way than human beings, clearly in an unconscious yet efficient manner.
Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-used and practically important class of cooperative games that inherently have a natural compact representation. We investigate the complexity of solution concepts for such games, and generalizations of them. We briefly discuss games with non-transferable utility and partition function games. We then overview algorithms for identifying welfare-maximizing coalition structures and methods used by rational agents to form coalitions (even under uncertainty), including bargaining algorithms. We conclude by considering some developing topics, applications, and future research directions.
Melvin Dresher, noted research mathematician for the Rand Corporation, puts forth an exceptionally clear presentation of the mathematical theory of games of strategy and its applications to many fields including: economics, military, business, and operations research. The mathematical presentation is elementary in the sense that no advanced algebra or non-elementary calculus occurs in most of the mathematical proofs.
The author presents game theory as a branch of applied mathematics. In addition to developing a mathematical theory for solving games, he shows how to formulate a game model associated with a given competitive or conflicting situation. Furthermore, he shows how some decision problems, such as timing of decisions, which do not resemble game situations, can be analyzed as a game, yielding rich insights into the decision problems.
Beginning with an exposition of games of strategy, with examples from parlor games as well as military games, Dr. Dresher proceeds to treat the basic topics in the theory of finite games, i.e., the existence of optimal strategies and their properties. An elementary proof of the minimax theorem is given that provides an efficient method for computing optimal strategies.
Since many games involve an infinite number of strategies, succeeding chapters deal with such games by first developing the necessary mathematics (e.g., probability distribution functions and Stieltjes integrals) for analyzing infinite games. The results of infinite games are then applied to two general classes of games — timing games and tactical games. A final chapter provides an application of moment space theory to the solution of infinite games.
This is a book about decision making in the absence of perfect information. In particular, it analyzes decision problems in a competitive environment where conflicting interests exist, and uncertainties and risk are involved. For the reader who is interested in the applications of the theory of games of strategy to military, economic, or political problems, or to decision making in business, operations research, or the behavior sciences, it will prove a most rewarding study.
"The best book available for non-mathematicians." — Contemporary Psychology.
This book represents the earliest clear, detailed, precise exposition of the central ideas and results of game theory and related decision-making models — unencumbered by technical mathematical details. It offers a comprehensive, time-tested conceptual introduction, with a social science orientation, to a complex of ideas related to game theory including decision theory, modern utility theory, the theory of statistical decisions, and the theory of social welfare functions.
The first three chapters provide a general introduction to the theory of games including utility theory. Chapter 4 treats two-person, zero-sum games. Chapters 5 and 6 treat two-person, nonzero-sum games and concepts developed in an attempt to meet some of the deficiencies in the von Neumann-Morgenstern theory. Chapters 7–12 treat n-person games beginning with the von Neumann-Morgenstern theory and reaching into many newer developments. The last two chapters, 13 and 14, discuss individual and group decision making. Eight helpful appendixes present proofs of the famous minimax theorem, several geometric interpretations of two-person zero-sum games, solution procedures, infinite games, sequential compounding of games, and linear programming.
Thought-provoking and clearly expressed, Games and Decisions: Introduction and Critical Survey is designed for the non-mathematician and requires no advanced mathematical training. It will be welcomed by economists concerned with economic theory, political scientists and sociologists dealing with conflict of interest, experimental psychologists studying decision making, management scientists, philosophers, statisticians, and a wide range of other decision-makers. It will likewise be indispensable for students in courses in the mathematical theory of games and linear programming.
Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-used and practically important class of cooperative games that inherently have a natural compact representation. We investigate the complexity of solution concepts for such games, and generalizations of them. We briefly discuss games with non-transferable utility and partition function games. We then overview algorithms for identifying welfare-maximizing coalition structures and methods used by rational agents to form coalitions (even under uncertainty), including bargaining algorithms. We conclude by considering some developing topics, applications, and future research directions.
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