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A Scenario Aggregation Algorithm For The Solution Of Stochastic Dynamic Minimax Problems
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Author :Breton, Michèle Publisher :Montréal : Groupe d'études et de recherche en analyse des décisions ISBN 13 : Total Pages :46 pages Book Rating :4.:/5 (262 download)
Book Synopsis A Scenario Aggregation Algorithm for the Solution of Stochastic Dynamic Minimax Problems by : Breton, Michèle
Download or read book A Scenario Aggregation Algorithm for the Solution of Stochastic Dynamic Minimax Problems written by Breton, Michèle and published by Montréal : Groupe d'études et de recherche en analyse des décisions. This book was released on 1992 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Breton, Michèle Publisher :Montréal : Groupe d'études et de recherche en analyse des décisions ISBN 13 : Total Pages :46 pages Book Rating :4.:/5 (268 download)
Book Synopsis Algorithms for the Solution of Stochastic Dynamic Minimax Problems by : Breton, Michèle
Download or read book Algorithms for the Solution of Stochastic Dynamic Minimax Problems written by Breton, Michèle and published by Montréal : Groupe d'études et de recherche en analyse des décisions. This book was released on 1992 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Theory and Method Abstracts by :
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 1996 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Reviews written by and published by . This book was released on 2003 with total page 1448 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Stochastic Algorithm for Minimax Problems by : Yuri Ermoliev
Download or read book A Stochastic Algorithm for Minimax Problems written by Yuri Ermoliev and published by . This book was released on 1982 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Global Algorithm for Minimax Solutions to a Stochastic Programming Problem by : Robert Dyson
Download or read book A Global Algorithm for Minimax Solutions to a Stochastic Programming Problem written by Robert Dyson and published by . This book was released on 1975 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Global Alogorithm [i.e. Algorithm] for Minimax Solutions to a Stochastic Programming Problem by : Robert Dyson
Download or read book A Global Alogorithm [i.e. Algorithm] for Minimax Solutions to a Stochastic Programming Problem written by Robert Dyson and published by . This book was released on 1975 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Christodoulos A. Floudas Publisher :Springer Science & Business Media ISBN 13 :0387747583 Total Pages :4646 pages Book Rating :4.3/5 (877 download)
Book Synopsis Encyclopedia of Optimization by : Christodoulos A. Floudas
Download or read book Encyclopedia of Optimization written by Christodoulos A. Floudas and published by Springer Science & Business Media. This book was released on 2008-09-04 with total page 4646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
Book Synopsis Algorithms for Reinforcement Learning by : Csaba Grossi
Download or read book Algorithms for Reinforcement Learning written by Csaba Grossi and published by Springer Nature. This book was released on 2022-05-31 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration
Book Synopsis Stochastic Decomposition by : Julia L. Higle
Download or read book Stochastic Decomposition written by Julia L. Higle and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP optimization models. There are several arenas model is appropriate, and such models have found applications in air line yield management, capacity planning, electric power generation planning, financial planning, logistics, telecommunications network planning, and many more. In some of these applications, modelers represent uncertainty in terms of only a few seenarios and formulate a large scale linear program which is then solved using LP software. However, there are many applications, such as the telecommunications planning problem discussed in this book, where a handful of seenarios do not capture variability well enough to provide a reasonable model of the actual decision-making problem. Problems of this type easily exceed the capabilities of LP software by several orders of magnitude. Their solution requires the use of algorithmic methods that exploit the structure of the SLP model in a manner that will accommodate large scale applications.
Book Synopsis Multistage Stochastic Optimization by : Georg Ch. Pflug
Download or read book Multistage Stochastic Optimization written by Georg Ch. Pflug and published by Springer. This book was released on 2014-11-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
Book Synopsis Decision and Game Theory for Security by : Tansu Alpcan
Download or read book Decision and Game Theory for Security written by Tansu Alpcan and published by Springer Nature. This book was released on 2019-10-23 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Decision and Game Theory for Security, GameSec 2019,held in Stockholm, Sweden, in October 2019.The 21 full papers presented together with 11 short papers were carefully reviewed and selected from 47 submissions.The papers focus on protection of heterogeneous, large-scale and dynamic cyber-physical systems as well as managing security risks faced by critical infrastructures through rigorous and practically-relevant analytical methods.
Book Synopsis Reinforcement Learning, second edition by : Richard S. Sutton
Download or read book Reinforcement Learning, second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Book Synopsis The Science and Management of Uncertainty by : Bruce G. Marcot
Download or read book The Science and Management of Uncertainty written by Bruce G. Marcot and published by CRC Press. This book was released on 2020-11-26 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty can take many forms, can be represented in many ways, and can have important implications in decision-making and policy development. This book provides a rigorous scientific framework for dealing with uncertainty in real-world situations, and provides a comprehensive study of concepts, measurements, and applications of uncertainty in ecological modeling and natural resource management. The focus of this book is on the kinds and implications of uncertainty in environmental modeling and management, with practical guidelines and examples for successful modeling and risk analysis in the face of uncertain conditions and incomplete information. Provided is a clear classification of uncertainty; methods for measuring, modeling, and communicating uncertainty; practical guidelines for capturing and representing expert knowledge and judgment; explanations of the role of uncertainty in decision-making; a guideline to avoiding logical fallacies when dealing with uncertainty; and several example cases of real-world ecological modeling and risk analysis to illustrate the concepts and approaches. Case topics provide examples of structured decision-making, statistical modeling, and related topics. A summary provides practical next steps that the reader can take in analyzing and interpreting uncertainty in real-world situations. Also provided is a glossary and a suite of references.
Book Synopsis Patterns, Predictions, and Actions: Foundations of Machine Learning by : Moritz Hardt
Download or read book Patterns, Predictions, and Actions: Foundations of Machine Learning written by Moritz Hardt and published by Princeton University Press. This book was released on 2022-08-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers
Book Synopsis Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems by : Sébastien Bubeck
Download or read book Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems written by Sébastien Bubeck and published by Now Pub. This book was released on 2012 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph, the focus is on two extreme cases in which the analysis of regret is particularly simple and elegant: independent and identically distributed payoffs and adversarial payoffs. Besides the basic setting of finitely many actions, it analyzes some of the most important variants and extensions, such as the contextual bandit model.
Download or read book Science Abstracts written by and published by . This book was released on 1993 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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