Leyton-Brown, Kevin.
Essentials of Game Theory A Concise Multidisciplinary Introduction / [electronic resource] : by Kevin Leyton-Brown, Yoav Shoham. - 1st ed. 2008. - XVI, 88 p. online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616 . - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
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.
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.
9783031015458
10.1007/978-3-031-01545-8 doi
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Q334-342 TA347.A78
006.3
Essentials of Game Theory A Concise Multidisciplinary Introduction / [electronic resource] : by Kevin Leyton-Brown, Yoav Shoham. - 1st ed. 2008. - XVI, 88 p. online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616 . - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
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.
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.
9783031015458
10.1007/978-3-031-01545-8 doi
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Q334-342 TA347.A78
006.3