Optimal learning / / Warren B. Powell, Ilya O. Ryzhov

• Autore: Powell Warren B. <1955->
• Pubblicazione: Hoboken, NJ, : Wiley, 2012
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (416 p.)
• Disciplina: 006.3/1
• Soggetto topico: Machine learning; Artificial intelligence
• Classificazione: MAT029000
• Altri autori: RyzhovIlya Olegovich <1985->
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Optimal Learning; CONTENTS; Preface; Acknowledgments; 1 The Challenges of Learning; 1.1 Learning the Best Path; 1.2 Areas of Application; 1.3 Major Problem Classes; 1.4 The Different Types of Learning; 1.5 Learning from Different Communities; 1.6 Information Collection Using Decision Trees; 1.6.1 A Basic Decision Tree; 1.6.2 Decision Tree for Offline Learning; 1.6.3 Decision Tree for Online Learning; 1.6.4 Discussion; 1.7 Website and Downloadable Software; 1.8 Goals of this Book; Problems; 2 Adaptive Learning; 2.1 The Frequentist View; 2.2 The Bayesian View ; 2.2.1 The Updating Equations for Independent Beliefs2.2.2 The Expected Value of Information; 2.2.3 Updating for Correlated Normal Priors; 2.2.4 Bayesian Updating with an Uninformative Prior; 2.3 Updating for Non-Gaussian Priors; 2.3.1 The Gamma-Exponential Model; 2.3.2 The Gamma-Poisson Model; 2.3.3 The Pareto-Uniform Model; 2.3.4 Models for Learning Probabilities*; 2.3.5 Learning an Unknown Variance*; 2.4 Monte Carlo Simulation; 2.5 Why Does It Work?*; 2.5.1 Derivation of σ; 2.5.2 Derivation of Bayesian Updating Equations for Independent Beliefs; 2.6 Bibliographic Notes; Problems ; 3 The Economics of Information3.1 An Elementary Information Problem; 3.2 The Marginal Value of Information; 3.3 An information Acquisition Problem; 3.4 Bibliographic Notes; Problems; 4 Ranking and Selection; 4.1 The Model; 4.2 Measurement Policies; 4.2.1 Deterministic Versus Sequential Policies; 4.2.2 Optimal Sequential Policies; 4.2.3 Heuristic Policies; 4.3 Evaluating Policies; 4.4 More Advanced Topics*; 4.4.1 An Alternative Representation of the Probability Space; 4.4.2 Equivalence of Using True Means and Sample Estimates; 4.5 Bibliographic Notes; Problems; 5 The Knowledge Gradient ; 5.1 The Knowledge Gradient for Independent Beliefs5.1.1 Computation; 5.1.2 Some Properties of the Knowledge Gradient; 5.1.3 The Four Distributions of Learning; 5.2 The Value of Information and the S-Curve Effect; 5.3 Knowledge Gradient for Correlated Beliefs; 5.4 Anticipatory Versus Experiential Learning; 5.5 The Knowledge Gradient for Some Non-Gaussian Distributions; 5.5.1 The Gamma-Exponential Model; 5.5.2 The Gamma-Poisson Model; 5.5.3 The Pareto-Uniform Model; 5.5.4 The Beta-Bernoulli Model; 5.5.5 Discussion; 5.6 Relatives of the Knowledge Gradient; 5.6.1 Expected Improvement ; 5.6.2 Linear Loss*5.7 The Problem of Priors; 5.8 Discussion; 5.9 Why Does It Work?*; 5.9.1 Derivation of the Knowledge Gradient Formula; 5.10 Bibliographic Notes; Problems; 6 Bandit Problems; 6.1 The Theory and Practice of Gittins Indices; 6.1.1 Gittins Indices in the Beta-Bernoulli Model; 6.1.2 Gittins Indices in the Normal-Normal Model; 6.1.3 Approximating Gittins Indices; 6.2 Variations of Bandit Problems; 6.3 Upper Confidence Bounding; 6.4 The Knowledge Gradient for Bandit Problems; 6.4.1 The Basic Idea; 6.4.2 Some Experimental Comparisons; 6.4.3 Non-Normal Models; 6.5 Bibliographic Notes ; Problems
• Sommario/riassunto: Learn the science of collecting information to make effective decisions Everyday decisions are made without the benefit of accurate information. Optimal Learning develops the needed principles for gathering information to make decisions, especially when collecting information is time-consuming and expensive. Designed for readers with an elementary background in probability and statistics, the book presents effective and practical policies illustrated in a wide range of applications, from energy, homeland security, and transportation to engineering, health, and business. T
• Titolo autorizzato: Optimal learning
• ISBN: 9786613622327; 9781118309841; 1118309847; 9781280592492; 1280592494; 9781118304532; 1118304535; 9781118309827; 1118309820; 9781118309858; 1118309855
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910810636103321
• Lo trovi qui: Univ. Federico II
• Serie: Wiley series in probability and statistics.