Game theory and its economic applications

2018 ◽  
Author(s):  
Анатолий Сигал ◽  
Anatoliy Sigal
Keyword(s):  
Game Theory ◽  
Matrix Games ◽  
Managerial Decisions ◽  
Combined Application ◽  
Finite Games ◽  
Basic Concepts ◽  
Zero Sum ◽  
Risk Managers ◽  
Large Groups ◽  
Antagonistic Games

The manual describes the main sections of game theory, the basic concepts of the theory of economic risks and the conceptual framework for modeling the process of making managerial decisions in the economy based on the combined application of statistical and antagonistic games. Antagonistic games (AG) are the finite games of two persons with zero sum, i.e. matrix games, with classical antagonistic games called AG, given by completely known matrices, and neoclassical antagonistic games – AG, given by partially known matrices. The manual is intended primarily for masters who study in the direction of training "business information". However, it will be useful for students and postgraduates studying in large groups of areas of training "Economics and Management", "Mathematics and Mechanics", "Management in Technical Systems", as well as scientific and pedagogical workers specializing in the field of the theory of games, risk managers , managers and economists-practitioners.

John von Neumann's Contribution to Modern Game Theory

2004 ◽  
Vol 54 (1) ◽  
pp. 73-84 ◽  
Author(s):  
Ferenc Forgó
Keyword(s):  
Game Theory ◽  
Cooperative Games ◽  
Minimax Theorem ◽  
Stable Set ◽  
Zero Sum Games ◽  
Side Payments ◽  
Basic Concepts ◽  
Definition Of ◽  
Zero Sum ◽  
Abstract Games

The paper gives a brief account of von Neumann's contribution to the foundation of game theory: definition of abstract games, the minimax theorem for two-person zero-sum games and the stable set solution for cooperative games with side payments. The presentation is self-contained, uses very little mathematical formalism and caters to the nonspecialist. Basic concepts and their implications are in focus. It is also indicated how von Neumann's groundbreaking work initiated further research, and a few unsolved problems are also mentioned.

Noncooperative Game Theory

2017 ◽  
Author(s):  
João P. Hespanha
Keyword(s):  
Game Theory ◽  
Computer Science ◽  
Dynamic Games ◽  
Design Methodology ◽  
Noncooperative Game ◽  
Noncooperative Game Theory ◽  
Original Design ◽  
Theoretical Perspectives ◽  
Engineering Designs ◽  
Zero Sum

This book is aimed at students interested in using game theory as a design methodology for solving problems in engineering and computer science. The book shows that such design challenges can be analyzed through game theoretical perspectives that help to pinpoint each problem's essence: Who are the players? What are their goals? Will the solution to “the game” solve the original design problem? Using the fundamentals of game theory, the book explores these issues and more. The use of game theory in technology design is a recent development arising from the intrinsic limitations of classical optimization-based designs. In optimization, one attempts to find values for parameters that minimize suitably defined criteria—such as monetary cost, energy consumption, or heat generated. However, in most engineering applications, there is always some uncertainty as to how the selected parameters will affect the final objective. Through a sequential and easy-to-understand discussion, the book examines how to make sure that the selection leads to acceptable performance, even in the presence of uncertainty—the unforgiving variable that can wreck engineering designs. The book looks at such standard topics as zero-sum, non-zero-sum, and dynamic games and includes a MATLAB guide to coding. This book offers students a fresh way of approaching engineering and computer science applications.

MONTE CARLO METHODS IN FUZZY GAME THEORY

2007 ◽  
Vol 03 (02) ◽  
pp. 259-269 ◽  
Author(s):  
AREEG ABDALLA ◽  
JAMES BUCKLEY
Keyword(s):  
Game Theory ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Monte Carlo Methods ◽  
Mixed Strategy ◽  
Minimax Theorem ◽  
Approximate Solutions ◽  
Mixed Strategies ◽  
Fuzzy Game ◽  
Zero Sum

In this paper, we consider a two-person zero-sum game with fuzzy payoffs and fuzzy mixed strategies for both players. We define the fuzzy value of the game for both players [Formula: see text] and also define an optimal fuzzy mixed strategy for both players. We then employ our fuzzy Monte Carlo method to produce approximate solutions, to an example fuzzy game, for the fuzzy values [Formula: see text] for Player I and [Formula: see text] for Player II; and also approximate solutions for the optimal fuzzy mixed strategies for both players. We then look at [Formula: see text] and [Formula: see text] to see if there is a Minimax theorem [Formula: see text] for this fuzzy game.

Basic Concepts in Game Theory

2020 ◽  
pp. 19-30
Author(s):  
Lone Grønbæk ◽  
Marko Lindroos ◽  
Gordon Munro ◽  
Pedro Pintassilgo
Keyword(s):  
Game Theory ◽  
Basic Concepts

Zero-sum game theory model for segmenting skin regions

2020 ◽  
Vol 99 ◽  
pp. 103925
Author(s):  
Djamila Dahmani ◽  
Mehdi Cheref ◽  
Slimane Larabi
Keyword(s):  
Game Theory ◽  
Theory Model ◽  
Zero Sum
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