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Design Of Experiments For Reinforcement Learning


Design Of Experiments For Reinforcement Learning
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Design Of Experiments For Reinforcement Learning


Design Of Experiments For Reinforcement Learning
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Author : Christopher Gatti
language : en
Publisher: Springer
Release Date : 2014-11-22

Design Of Experiments For Reinforcement Learning written by Christopher Gatti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-22 with Technology & Engineering categories.


This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge. The author approaches these entities using design of experiments not commonly employed to study machine learning methods. The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems.



Statistical Modeling And Simulation For Experimental Design And Machine Learning Applications


Statistical Modeling And Simulation For Experimental Design And Machine Learning Applications
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Author : Jürgen Pilz
language : en
Publisher: Springer Nature
Release Date : 2023-10-19

Statistical Modeling And Simulation For Experimental Design And Machine Learning Applications written by Jürgen Pilz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-19 with Mathematics categories.


This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and testing problems, the design of experiments, reliability and queueing theory, inventory analysis, and the interplay between statistical inference, machine learning methods and related applications. The refereed contributions originate from the 10th International Workshop on Simulation and Statistics, SimStat 2019, which was held in Salzburg, Austria, September 2–6, 2019, and were either presented at the conference or developed afterwards, relating closely to the topics of the workshop. The book is intended for statisticians and Ph.D. students who seek current developments and applications in the field.



The Design Of Experiments


The Design Of Experiments
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Author : R. Mead
language : en
Publisher: Cambridge University Press
Release Date : 1990-07-26

The Design Of Experiments written by R. Mead and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-07-26 with Mathematics categories.


In all the experimental sciences, good design of experiments is crucial to the success of research. Well-planned experiments can provide a great deal of information efficiently and can be used to test several hypotheses simultaneously. This book is about the statistical principles of good experimental design and is intended for all applied statisticians and practising scientists engaged in the design, implementation and analysis of experiments. Professor Mead has written the book with the emphasis on the logical principles of statistical design and employs a minimum of mathematics. Throughout he assumes that the large-scale analysis of data will be performed by computers and he is thus able to devote more attention to discussions of how all of the available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from medicine, agriculture, industry and other disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design of experiments can make to a scientific project.



Design Of Experiments For Engineers And Scientists


Design Of Experiments For Engineers And Scientists
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Author : Jiju Antony
language : en
Publisher: Elsevier
Release Date : 2014-02-22

Design Of Experiments For Engineers And Scientists written by Jiju Antony and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-22 with Technology & Engineering categories.


The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation.Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as through using statistical methods and readers will find the concepts in this book both familiar and easy to understand.This new edition includes a chapter on the role of DoE within Six Sigma methodology and also shows through the use of simple case studies its importance in the service industry. It is essential reading for engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. - Written in non-statistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE - Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem solving methodology - New edition includes a full chapter on DoE for services as well as case studies illustrating its wider application in the service industry



Advanced Lectures On Machine Learning


Advanced Lectures On Machine Learning
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Author : Olivier Bousquet
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-09-02

Advanced Lectures On Machine Learning written by Olivier Bousquet and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-02 with Computers categories.


Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references. Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.



Design Of Experiments For Reliability Achievement


Design Of Experiments For Reliability Achievement
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Author : Steven E. Rigdon
language : en
Publisher: John Wiley & Sons
Release Date : 2022-05-04

Design Of Experiments For Reliability Achievement written by Steven E. Rigdon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Science categories.


ENABLES READERS TO UNDERSTAND THE METHODS OF EXPERIMENTAL DESIGN TO SUCCESSFULLY CONDUCT LIFE TESTING TO IMPROVE PRODUCT RELIABILITY This book illustrates how experimental design and life testing can be used to understand product reliability in order to enable reliability improvements. The book is divided into four sections. The first section focuses on statistical distributions and methods for modeling reliability data. The second section provides an overview of design of experiments including response surface methodology and optimal designs. The third section describes regression models for reliability analysis focused on lifetime data. This section provides the methods for how data collected in a designed experiment can be properly analyzed. The final section of the book pulls together all of the prior sections with customized experiments that are uniquely suited for reliability testing. Throughout the text, there is a focus on reliability applications and methods. It addresses both optimal and robust design with censored data. To aid in reader comprehension, examples and case studies are included throughout the text to illustrate the key factors in designing experiments and emphasize how experiments involving life testing are inherently different. The book provides numerous state-of-the-art exercises and solutions to help readers better understand the real-world applications of experimental design and reliability. The authors utilize R and JMP® software throughout as appropriate, and a supplemental website contains the related data sets. Written by internationally known experts in the fields of experimental design methodology and reliability data analysis, sample topics covered in the book include: An introduction to reliability, lifetime distributions, censoring, and inference for parameter of lifetime distributions Design of experiments, optimal design, and robust design Lifetime regression, parametric regression models, and the Cox Proportional Hazard Model Design strategies for reliability achievement Accelerated testing, models for acceleration, and design of experiments for accelerated testing The text features an accessible approach to reliability for readers with various levels of technical expertise. This book is a key reference for statistical researchers, reliability engineers, quality engineers, and professionals in applied statistics and engineering. It is a comprehensive textbook for upper-undergraduate and graduate-level courses in statistics and engineering.



Computer Assisted Experiment Design In Psychology


Computer Assisted Experiment Design In Psychology
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Author : St. Clements University Academic Staff - Türkiye
language : en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date :

Computer Assisted Experiment Design In Psychology written by St. Clements University Academic Staff - Türkiye and has been published by Prof. Dr. Bilal Semih Bozdemir this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.


Computer-Assisted Experiment Design in Psychology The Need for Efficient Experiment Design Understanding Experiment Design Challenges Limitations of Traditional Experiment Design Methods Introducing Computer-Assisted Experiment Design Benefits of Computer-Assisted Experiment Design Improved Statistical Power and Precision Enhanced Experimental Control and Validity Reduced Time and Resources for Experiment Execution Optimized Participant Recruitment and Allocation Key Considerations in Computer-Assisted Experiment Design Experimental Variables and Hypotheses Identifying Independent and Dependent Variables Establishing Appropriate Control Conditions Minimizing Confounding Factors Designing Data Collection Protocols Selecting Appropriate Outcome Measures Ensuring Ethical Considerations Leveraging Computational Algorithms in Experiment Design Factorial Designs and Response Surface Methodology Adaptive Designs and Sequential Experimentation Bayesian Optimization and Adaptive Randomization Machine Learning Approaches in Experiment Design Case Studies in Computer-Assisted Experiment Design Improving Clinical Trial Design and Efficiency Enhancing Behavioral Intervention Studies Optimizing User Experience Research Integrating Computer-Assisted Design with Existing Workflows Overcoming Challenges and Limitations Ensuring Reproducibility and Transparency Addressing Regulatory Concerns and Best Practices Ethical Considerations in Automated Experiment Design Training and Upskilling Researchers Collaboration between Researchers and Computer Scientists The Future of Computer-Assisted Experiment Design Emerging Trends and Innovations Integrating with Artificial Intelligence and Machine Learning Enhancing Interdisciplinary Collaboration Expanding Applications beyond Psychology Ensuring Responsible and Equitable Implementation Conclusion: Unlocking the Potential of Computer-Assisted Experiment Design



Statistical Machine Learning For Engineering With Applications


Statistical Machine Learning For Engineering With Applications
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Author : Jürgen Franke
language : en
Publisher: Springer Nature
Release Date : 2024-10-08

Statistical Machine Learning For Engineering With Applications written by Jürgen Franke and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-08 with Mathematics categories.


This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For ease of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed. The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis. The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students.



Ai Guided Design And Property Prediction For Zeolites And Nanoporous Materials


Ai Guided Design And Property Prediction For Zeolites And Nanoporous Materials
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Author : German Sastre
language : en
Publisher: John Wiley & Sons
Release Date : 2023-01-25

Ai Guided Design And Property Prediction For Zeolites And Nanoporous Materials written by German Sastre and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-25 with Science categories.


AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials A cohesive and insightful compilation of resources explaining the latest discoveries and methods in the field of nanoporous materials In Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction a team of distinguished researchers delivers a robust compilation of the latest knowledge and most recent developments in computational chemistry, synthetic chemistry, and artificial intelligence as it applies to zeolites, porous molecular materials, covalent organic frameworks and metal-organic frameworks. The book presents a common language that unifies these fields of research and advances the discovery of new nanoporous materials. The editors have included resources that describe strategies to synthesize new nanoporous materials, construct databases of materials, structure directing agents, and synthesis conditions, and explain computational methods to generate new materials. They also offer material that discusses AI and machine learning algorithms, as well as other, similar approaches to the field. Readers will also find a comprehensive approach to artificial intelligence applied to and written in the language of materials chemistry, guiding the reader through the fundamental questions on how far computer algorithms and numerical representations can drive our search of new nanoporous materials for specific applications. Designed for academic researchers and industry professionals with an interest in synthetic nanoporous materials chemistry, Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction will also earn a place in the libraries of professionals working in large energy, chemical, and biochemical companies with responsibilities related to the design of new nanoporous materials.



Virtual Materials Design


Virtual Materials Design
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Author : Norbert Huber
language : en
Publisher: Frontiers Media SA
Release Date : 2022-08-02

Virtual Materials Design written by Norbert Huber and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-02 with Technology & Engineering categories.