Essentials of Game Theory A Concise Multidisciplinary Introduction /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Leyton-Brown, Kevin (Autor), Shoham, Yoav (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Synthesis Lectures on Artificial Intelligence and Machine Learning,
Temas:
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Essentials of Game Theory  |h [electronic resource] :  |b A Concise Multidisciplinary Introduction /  |c by Kevin Leyton-Brown, Yoav Shoham. 
250 |a 1st ed. 2008. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2008. 
300 |a XVI, 88 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Synthesis Lectures on Artificial Intelligence and Machine Learning,  |x 1939-4616 
505 0 |a 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. 
520 |a 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. 
650 0 |a Artificial intelligence. 
650 0 |a Machine learning. 
650 0 |a Neural networks (Computer science) . 
650 1 4 |a Artificial Intelligence. 
650 2 4 |a Machine Learning. 
650 2 4 |a Mathematical Models of Cognitive Processes and Neural Networks. 
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776 0 8 |i Printed edition:  |z 9783031000201 
776 0 8 |i Printed edition:  |z 9783031004179 
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830 0 |a Synthesis Lectures on Artificial Intelligence and Machine Learning,  |x 1939-4616 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-031-01545-8  |z Texto Completo 
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