EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book Learning based Model Predictive Control with closed loop guarantees

Download or read book Learning based Model Predictive Control with closed loop guarantees written by Raffaele Soloperto and published by Logos Verlag Berlin GmbH. This book was released on 2023-11-13 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: The performance of model predictive control (MPC) largely depends on the accuracy of the prediction model and of the constraints the system is subject to. However, obtaining an accurate knowledge of these elements might be expensive in terms of money and resources, if at all possible. In this thesis, we develop novel learning-based MPC frameworks that actively incentivize learning of the underlying system dynamics and of the constraints, while ensuring recursive feasibility, constraint satisfaction, and performance bounds for the closed-loop. In the first part, we focus on the case of inaccurate models, and analyze learning-based MPC schemes that include, in addition to the primary cost, a learning cost that aims at generating informative data by inducing excitation in the system. In particular, we first propose a nonlinear MPC framework that ensures desired performance bounds for the resulting closed-loop, and then we focus on linear systems subject to uncertain parameters and noisy output measurements. In order to ensure that the desired learning phase occurs in closed-loop operations, we then propose an MPC framework that is able to guarantee closed-loop learning of the controlled system. In the last part of the thesis, we investigate the scenario where the system is known but evolves in a partially unknown environment. In such a setup, we focus on a learning-based MPC scheme that incentivizes safe exploration if and only if this might yield to a performance improvement.

Book Integrated Uncertainty in Knowledge Modelling and Decision Making

Download or read book Integrated Uncertainty in Knowledge Modelling and Decision Making written by Van-Nam Huynh and published by Springer Nature. This book was released on 2023-10-26 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.

Book Analysis and Decision Making in Uncertain Systems

Download or read book Analysis and Decision Making in Uncertain Systems written by Zdzislaw Bubnicki and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified and systematic description of analysis and decision problems within a wide class of uncertain systems, described by traditional mathematical methods and by relational knowledge representations. Prof. Bubnicki takes a unique approach to stability and stabilization of uncertain systems.

Book Model Validation and Uncertainty Quantification  Volume 3

Download or read book Model Validation and Uncertainty Quantification Volume 3 written by Robert Barthorpe and published by Springer. This book was released on 2017-06-07 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty

Book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging written by Carole H. Sudre and published by Springer Nature. This book was released on 2023-10-06 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. For this workshop, 21 papers from 32 submissions were accepted for publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.

Book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging  and Graphs in Biomedical Image Analysis

Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Graphs in Biomedical Image Analysis written by Carole H. Sudre and published by Springer Nature. This book was released on 2020-10-05 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

Book Uncertainty in Artificial Intelligence

Download or read book Uncertainty in Artificial Intelligence written by David Heckerman and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.

Book Feedback Control Theory

Download or read book Feedback Control Theory written by John C. Doyle and published by Courier Corporation. This book was released on 2013-04-09 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: An excellent introduction to feedback control system design, this book offers a theoretical approach that captures the essential issues and can be applied to a wide range of practical problems. Its explorations of recent developments in the field emphasize the relationship of new procedures to classical control theory, with a focus on single input and output systems that keeps concepts accessible to students with limited backgrounds. The text is geared toward a single-semester senior course or a graduate-level class for students of electrical engineering. The opening chapters constitute a basic treatment of feedback design. Topics include a detailed formulation of the control design program, the fundamental issue of performance/stability robustness tradeoff, and the graphical design technique of loopshaping. Subsequent chapters extend the discussion of the loopshaping technique and connect it with notions of optimality. Concluding chapters examine controller design via optimization, offering a mathematical approach that is useful for multivariable systems.

Book Learning Pathways within the Multiplicative Conceptual Field

Download or read book Learning Pathways within the Multiplicative Conceptual Field written by Caroline Long and published by Waxmann Verlag. This book was released on 2015 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: The transition from whole numbers to rational numbers and the associated mastery of the multiplicative conceptual field constitute an important development in lower secondary schooling. This study draws primarily on the theory of conceptual fields as a framework that is mathematical and enables a cognitive perspective by identifying the concepts- and theorems-in-action that lead to underlying concepts and theorems. Application of the Rasch model configures the location of both item difficulty and learner proficiency on one scale. Diagnostics explore the validity of the instrument for measurement. The ordering of items enables the analysis of hierarchical conceptual strands and additional insights into the mastery of concepts by subsets of learners at particular levels. The resulting matrix, of interactions of learner proficiency and item complexity, provides an overview of the concepts attained and not yet mastered. These insights permit teacher interventions specific to each learner subset at a shared common current zone of proximal development along the scale. Caroline Long has received her doctorate in Mathematics Education from the University of Cape Town in 2011 and is Senior Lecturer in the Faculty of Education at the University of Pretoria, where she is responsible for teaching mathematics education courses, and modules on assessment. She is also Deputy Director at the Centre for Evaluation and Assessment. Her primary research foci are mathematics education, professional development, teacher agency and assessment. Current work relies on collaboration with researchers at other South African institutions, and in Australia, Canada, England, Germany, India, the Netherlands, Scotland and the USA.

Book Robustness

    Book Details:
  • Author : Lars Peter Hansen
  • Publisher : Princeton University Press
  • Release : 2016-06-28
  • ISBN : 0691170975
  • Pages : 453 pages

Download or read book Robustness written by Lars Peter Hansen and published by Princeton University Press. This book was released on 2016-06-28 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.

Book CIMA Official Learning System Fundamentals of Business Mathematics

Download or read book CIMA Official Learning System Fundamentals of Business Mathematics written by Graham Eaton and published by Elsevier. This book was released on 2009-07-18 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: CIMA Official Learning Systems are the only coursebooks recommended by CIMA. Written by a team of experts that include past and present CIMA examiners and markers, they contain everything you need to know. Each book maps to the syllabus chapter by chapter to help you learn effectively and reinforce learning with features including: - comprehensive coverage of the whole syllabus - step by step coverage directly linked to CIMA's Learning Outcomes - up to date examples and case studies - practice questions to test knowledge and understanding - integrated readings to increase understanding of key theories - colour used throughout to highlight key learning points * The Official Learning systems are the only study materials endorsed by CIMA * Key sections written by former examiners for the most accurate, up-to-date guidance towards exam success * Complete integrated package incorporating syllabus guidance, full text, recommended articles, revision guides and extensive question practice

Book Robotics  AI  and Humanity

Download or read book Robotics AI and Humanity written by Joachim von Braun and published by Springer Nature. This book was released on 2021-02-12 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book examines recent advances in how artificial intelligence (AI) and robotics have elicited widespread debate over their benefits and drawbacks for humanity. The emergent technologies have for instance implications within medicine and health care, employment, transport, manufacturing, agriculture, and armed conflict. While there has been considerable attention devoted to robotics/AI applications in each of these domains, a fuller picture of their connections and the possible consequences for our shared humanity seems needed. This volume covers multidisciplinary research, examines current research frontiers in AI/robotics and likely impacts on societal well-being, human – robot relationships, as well as the opportunities and risks for sustainable development and peace. The attendant ethical and religious dimensions of these technologies are addressed and implications for regulatory policies on the use and future development of AI/robotics technologies are elaborated.

Book Resources in Education

Download or read book Resources in Education written by and published by . This book was released on 1997 with total page 1032 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Scientific and Technical Aerospace Reports

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 1572 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Mental Models and Their Dynamics  Adaptation  and Control

Download or read book Mental Models and Their Dynamics Adaptation and Control written by Jan Treur and published by Springer Nature. This book was released on 2022-01-26 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a generic approach to model the use and adaptation of mental models, including the control over this. In their mental processes, humans often make use of internal mental models as a kind of blueprints for processes that can take place in the world or in other persons. By internal mental simulation of such a mental model in their brain, they can predict and be prepared for what can happen in the future. Usually, mental models are adaptive: they can be learned, refined, revised, or forgotten, for example. Although there is a huge literature on mental models in various disciplines, a systematic account of how to model them computationally in a transparent manner is lacking. This approach allows for computational modeling of humans using mental models without a need for any algorithmic or programming skills, allowing for focus on the process of conceptualizing, modeling, and simulating complex, real-world mental processes and behaviors. The book is suitable for and is used as course material for multidisciplinary Master and Ph.D. students.

Book INFORMS Annual Meeting

Download or read book INFORMS Annual Meeting written by Institute for Operations Research and the Management Sciences. National Meeting and published by . This book was released on 2009 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Machine Learning and Knowledge Discovery in Databases

Download or read book Machine Learning and Knowledge Discovery in Databases written by Annalisa Appice and published by Springer. This book was released on 2015-08-28 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, and 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.