Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Information Science Reference, 2011
ISBN 10: 1609601653 ISBN 13: 9781609601652
Idioma: Inglés
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 183,92
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Publicado por IGI Global (edition 1), 2011
ISBN 10: 1609601653 ISBN 13: 9781609601652
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 162,01
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Añadir al carritoHardcover. Condición: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 228,70
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Publicado por Information Science Reference, 2011
ISBN 10: 1609601653 ISBN 13: 9781609601652
Idioma: Inglés
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 175,39
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Publicado por Springer US, Springer US, 2012
ISBN 10: 1461372836 ISBN 13: 9781461372837
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 238,64
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.
Publicado por Springer US, Springer US, 1999
ISBN 10: 0792385349 ISBN 13: 9780792385349
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 246,77
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 219,08
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 219,32
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 189,36
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Añadir al carritoHRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 194,85
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por Information Science Reference, 2011
ISBN 10: 1609601653 ISBN 13: 9781609601652
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 195,01
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages .
Publicado por Information Science Reference, 2011
ISBN 10: 1609601653 ISBN 13: 9781609601652
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 243,28
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.