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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 39,92
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Añadir al carritoPaperback or Softback. Condición: New. Multi-Objective Decision Making. Book.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 36,86
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Publicado por Springer International Publishing AG, CH, 2017
ISBN 10: 3031004485 ISBN 13: 9783031004483
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 41,82
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Añadir al carritoPaperback. Condición: New. 1°. Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs).First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the availableinformation about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems.Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting.Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 42,56
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Añadir al carritoCondición: New.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 33,83
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Añadir al carritoCondición: New. In English.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 45,75
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Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
EUR 35,08
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Añadir al carritoPF. Condición: New.
EUR 28,53
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Añadir al carritoCondición: NEW.
EUR 75,32
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Añadir al carritoPaperback. Condición: Brand New. 129 pages. 9.50x7.50x0.25 inches. In Stock.
Publicado por Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2017
ISBN 10: 3031004485 ISBN 13: 9783031004483
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 37,61
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Añadir al carritoCondición: New. Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can ofte.
Publicado por Springer International Publishing AG, CH, 2017
ISBN 10: 3031004485 ISBN 13: 9783031004483
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
EUR 37,79
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Añadir al carritoPaperback. Condición: New. 1°. Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs).First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the availableinformation about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems.Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting.Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 36,55
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Añadir al carritoPaperback. Condición: Brand New. 128 pages. 9.25x7.51x9.25 inches. In Stock. This item is printed on demand.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 45,99
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Añadir al carritoCondición: New. Print on Demand.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 47,68
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Añadir al carritoCondición: New. PRINT ON DEMAND.