Optimal Search With Learning

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Optimal Learning

Author : Warren B. Powell
Publisher : John Wiley & Sons
ISBN 13 : 1118309847
Total Pages : 416 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Optimal Learning by : Warren B. Powell

Download or read book Optimal Learning written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2013-07-09 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. This book covers the fundamental dimensions of a learning problem and presents a simple method for testing and comparing policies for learning. Special attention is given to the knowledge gradient policy and its use with a wide range of belief models, including lookup table and parametric and for online and offline problems. Three sections develop ideas with increasing levels of sophistication: Fundamentals explores fundamental topics, including adaptive learning, ranking and selection, the knowledge gradient, and bandit problems Extensions and Applications features coverage of linear belief models, subset selection models, scalar function optimization, optimal bidding, and stopping problems Advanced Topics explores complex methods including simulation optimization, active learning in mathematical programming, and optimal continuous measurements Each chapter identifies a specific learning problem, presents the related, practical algorithms for implementation, and concludes with numerous exercises. A related website features additional applications and downloadable software, including MATLAB and the Optimal Learning Calculator, a spreadsheet-based package that provides an introduction to learning and a variety of policies for learning.

Reinforcement Learning and Optimal Control

Author : Dimitri P. Bertsekas
Publisher :
ISBN 13 : 9787302540328
Total Pages : 373 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Reinforcement Learning and Optimal Control by : Dimitri P. Bertsekas

Download or read book Reinforcement Learning and Optimal Control written by Dimitri P. Bertsekas and published by . This book was released on 2020 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Search in Artificial Intelligence

Author : Leveen Kanal
Publisher : Springer Science & Business Media
ISBN 13 : 1461387884
Total Pages : 491 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Search in Artificial Intelligence by : Leveen Kanal

Download or read book Search in Artificial Intelligence written by Leveen Kanal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.

Learning and Intelligent Optimization

Author : Nikolaos F. Matsatsinis
Publisher : Springer Nature
ISBN 13 : 3030386295
Total Pages : 412 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Learning and Intelligent Optimization by : Nikolaos F. Matsatsinis

Download or read book Learning and Intelligent Optimization written by Nikolaos F. Matsatsinis and published by Springer Nature. This book was released on 2020-01-21 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed pChania, Crete, Greece, in May 2019. The 38 full papers presented have been carefully reviewed and selected from 52 submissions. The papers focus on advancedresearch developments in such interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence and describe advanced ideas, technologies, methods, and applications in optimization and machine learning.

Optimization and Learning

Author : Bernabé Dorronsoro
Publisher : Springer Nature
ISBN 13 : 3030856720
Total Pages : 377 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Optimization and Learning by : Bernabé Dorronsoro

Download or read book Optimization and Learning written by Bernabé Dorronsoro and published by Springer Nature. This book was released on 2021-08-16 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 4th International Conference on Optimization and Learning, OLA 2021, held in Catania, Italy, in June 2021. Due to the COVID-19 pandemic the conference was held online. The 27 full papers were carefully reviewed and selected from 62 submissions. The papers presented in the volume are organized in topical sections on synergies between optimization and learning; learning for optimization; machine learning and deep learning; transportation and logistics; optimization; applications of learning and optimization methods.

Learning and Intelligent Optimization

Author : Ilias S. Kotsireas
Publisher : Springer Nature
ISBN 13 : 3030535525
Total Pages : 443 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Learning and Intelligent Optimization by : Ilias S. Kotsireas

Download or read book Learning and Intelligent Optimization written by Ilias S. Kotsireas and published by Springer Nature. This book was released on 2020-07-17 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings on Learning and Intelligent Optimization, LION 14, held in Athens, Greece, in May 2020. The 37 full papers presented together with one invited paper have been carefully reviewed and selected from 75 submissions. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components. Due to the COVID-19 pandemic, LION 14 was not held as a physical meeting.

Learning and Intelligent Optimization

Author : Roberto Battiti
Publisher : Springer
ISBN 13 : 3319694049
Total Pages : 401 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Learning and Intelligent Optimization by : Roberto Battiti

Download or read book Learning and Intelligent Optimization written by Roberto Battiti and published by Springer. This book was released on 2017-10-25 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Learning and Intelligent Optimization, LION 11, held in Nizhny,Novgorod, Russia, in June 2017. The 20 full papers (among these one GENOPT paper) and 15 short papers presented have been carefully reviewed and selected from 73 submissions. The papers explore the advanced research developments in such interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and applications in optimization and machine learning.

Automated Machine Learning

Author : Frank Hutter
Publisher : Springer
ISBN 13 : 3030053180
Total Pages : 223 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Automated Machine Learning by : Frank Hutter

Download or read book Automated Machine Learning written by Frank Hutter and published by Springer. This book was released on 2019-05-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Adaptivity and Learning

Author : Reimer Kühn
Publisher : Springer Science & Business Media
ISBN 13 : 3662055945
Total Pages : 400 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Adaptivity and Learning by : Reimer Kühn

Download or read book Adaptivity and Learning written by Reimer Kühn and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.

Simulated Evolution and Learning

Author : Xiaodong Li
Publisher : Springer Science & Business Media
ISBN 13 : 3540896937
Total Pages : 672 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Simulated Evolution and Learning by : Xiaodong Li

Download or read book Simulated Evolution and Learning written by Xiaodong Li and published by Springer Science & Business Media. This book was released on 2008-11-19 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers presented were carefully reviewed and selected from 140 submissions. The topics covered are evolutionary learning; evolutionary optimisation; hybrid learning; adaptive systems; theoretical issues in evolutionary computation; and real-world applications of evolutionary computation techniques.

Handbook of Applied Cognition

Author : Francis T. Durso
Publisher : John Wiley & Sons
ISBN 13 : 047005963X
Total Pages : 918 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Handbook of Applied Cognition by : Francis T. Durso

Download or read book Handbook of Applied Cognition written by Francis T. Durso and published by John Wiley & Sons. This book was released on 2007-02-06 with total page 918 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a team of leading international researchers under the guidance of Frank Durso, the second edition of the Handbook of Applied Cognition brings together the latest research into this challenging and important field, and is presented across thirty stimulating and accessible chapters. Stewarded by experiences editors from around the globe, the handbook has been fully updated with eleven new chapters covering materials that focus on the topics critical to understanding human mental functions in complex environments. It is an essential single-source reference for researchers, cognitive engineers and applied cognitive psychologists, as well as advanced students in the flourishing field of applied cognition.

Reinforcement Learning, second edition

Author : Richard S. Sutton
Publisher : MIT Press
ISBN 13 : 0262352702
Total Pages : 549 pages
Book Rating : 4.2/5 (623 download)

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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.

New Frontiers in Artificial Intelligence

Author : Takashi Onoda
Publisher : Springer Science & Business Media
ISBN 13 : 3642256546
Total Pages : 351 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis New Frontiers in Artificial Intelligence by : Takashi Onoda

Download or read book New Frontiers in Artificial Intelligence written by Takashi Onoda and published by Springer Science & Business Media. This book was released on 2012-01-10 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of four workshops held as satellite events of the JSAI International Symposia on Artificial Intelligence 2010, in Tokyo, Japan, in November 2010. The 28 revised full papers with four papers for the following four workshops presented were carefully reviewed and selected from 70 papers. The papers are organized in sections Logic and Engineering of Natural Language Semantics (LENLS), Juris-Informatics (JURISIN), Advanced Methodologies for Bayesian Networks (AMBN), and Innovating Service Systems (ISS).

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard
Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

100 Optimization Techniques

Author : Subrata Pandey
Publisher : SUBRATA PANDEY
ISBN 13 :
Total Pages : 103 pages
Book Rating : 4./5 ( download)

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Book Synopsis 100 Optimization Techniques by : Subrata Pandey

Download or read book 100 Optimization Techniques written by Subrata Pandey and published by SUBRATA PANDEY. This book was released on 2023-02-23 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: 100 optimization techniques is intended as a handbook for optimization techniques. Optimization techniques and algorithms are methods used to find the most efficient solution to a problem. Different techniques and algorithms may be used to solve a particular problem, depending on the nature of the problem. Researchers from varieties of domains are using optimization algorithms to solve problems in their domain. Different optimization techniques have their pros and cons. This book serves as a handbook for researchers who wants to know about different optimization methods currently available and their operating principles. One hundred optimization techniques are arranged in an alphabetical order. Researchers and students who want to use different optimization techniques for solving their domain related problems will find this book helpful.

Intelligent Computing and Optimization

Author : Pandian Vasant
Publisher : Springer Nature
ISBN 13 : 3031501519
Total Pages : 456 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Intelligent Computing and Optimization by : Pandian Vasant

Download or read book Intelligent Computing and Optimization written by Pandian Vasant and published by Springer Nature. This book was released on 2023-12-14 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment.

Handbook of Game Theory and Industrial Organization, Volume II

Author : Luis C. Corchón
Publisher : Edward Elgar Publishing
ISBN 13 : 1788112784
Total Pages : 547 pages
Book Rating : 4.7/5 (881 download)

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Book Synopsis Handbook of Game Theory and Industrial Organization, Volume II by : Luis C. Corchón

Download or read book Handbook of Game Theory and Industrial Organization, Volume II written by Luis C. Corchón and published by Edward Elgar Publishing. This book was released on 2018-02-23 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second volume of the Handbook includes original contribution by experts in the field. It provides up-to-date surveys of the most relevant applications of game theory to industrial organization. The book covers both classical as well as new IO topics such as mergers in markets with homogeneous and differentiated goods, leniency and coordinated effects in cartels and mergers, static and dynamic contests, consumer search and product safety, strategic delegation, platforms and network effects, auctions, environmental and resource economics, intellectual property, healthcare, corruption, experimental industrial organization and empirical models of R&D.