Autonomous Learning Systems

Autonomous Learning Systems

Author: Plamen Angelov

Publisher: John Wiley & Sons

Published: 2012-11-06

Total Pages: 259

ISBN-13: 1118481917

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Autonomous Learning Systems is the result of over a decade of focused research and studies in this emerging area which spans a number of well-known and well-established disciplines that include machine learning, system identification, data mining, fuzzy logic, neural networks, neuro-fuzzy systems, control theory and pattern recognition. The evolution of these systems has been both industry-driven with an increasing demand from sectors such as defence and security, aerospace and advanced process industries, bio-medicine and intelligent transportation, as well as research-driven – there is a strong trend of innovation of all of the above well-established research disciplines that is linked to their on-line and real-time application; their adaptability and flexibility. Providing an introduction to the key technologies, detailed technical explanations of the methodology, and an illustration of the practical relevance of the approach with a wide range of applications, this book addresses the challenges of autonomous learning systems with a systematic approach that lays the foundations for a fast growing area of research that will underpin a range of technological applications vital to both industry and society. Key features: Presents the subject systematically from explaining the fundamentals to illustrating the proposed approach with numerous applications. Covers a wide range of applications in fields including unmanned vehicles/robotics, oil refineries, chemical industry, evolving user behaviour and activity recognition. Reviews traditional fields including clustering, classification, control, fault detection and anomaly detection, filtering and estimation through the prism of evolving and autonomously learning mechanisms. Accompanied by a website hosting additional material, including the software toolbox and lecture notes. Autonomous Learning Systems provides a ‘one-stop shop’ on the subject for academics, students, researchers and practicing engineers. It is also a valuable reference for Government agencies and software developers.


Book Synopsis Autonomous Learning Systems by : Plamen Angelov

Download or read book Autonomous Learning Systems written by Plamen Angelov and published by John Wiley & Sons. This book was released on 2012-11-06 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous Learning Systems is the result of over a decade of focused research and studies in this emerging area which spans a number of well-known and well-established disciplines that include machine learning, system identification, data mining, fuzzy logic, neural networks, neuro-fuzzy systems, control theory and pattern recognition. The evolution of these systems has been both industry-driven with an increasing demand from sectors such as defence and security, aerospace and advanced process industries, bio-medicine and intelligent transportation, as well as research-driven – there is a strong trend of innovation of all of the above well-established research disciplines that is linked to their on-line and real-time application; their adaptability and flexibility. Providing an introduction to the key technologies, detailed technical explanations of the methodology, and an illustration of the practical relevance of the approach with a wide range of applications, this book addresses the challenges of autonomous learning systems with a systematic approach that lays the foundations for a fast growing area of research that will underpin a range of technological applications vital to both industry and society. Key features: Presents the subject systematically from explaining the fundamentals to illustrating the proposed approach with numerous applications. Covers a wide range of applications in fields including unmanned vehicles/robotics, oil refineries, chemical industry, evolving user behaviour and activity recognition. Reviews traditional fields including clustering, classification, control, fault detection and anomaly detection, filtering and estimation through the prism of evolving and autonomously learning mechanisms. Accompanied by a website hosting additional material, including the software toolbox and lecture notes. Autonomous Learning Systems provides a ‘one-stop shop’ on the subject for academics, students, researchers and practicing engineers. It is also a valuable reference for Government agencies and software developers.

Autonomous Learning from the Environment

Autonomous Learning from the Environment

Author: Wei-Min Shen

Publisher: Computer Science Press, Incorporated

Published: 1994

Total Pages: 355

ISBN-13: 9780716782650

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A significant contribution to the scientific foundation of autonomous learning systems, this book contains clear, up-to-date coverage of three basic subtasks: active model abstraction, model application, and integration. It is the only textbook to offer a thorough discussion of active model abstraction.


Book Synopsis Autonomous Learning from the Environment by : Wei-Min Shen

Download or read book Autonomous Learning from the Environment written by Wei-Min Shen and published by Computer Science Press, Incorporated. This book was released on 1994 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: A significant contribution to the scientific foundation of autonomous learning systems, this book contains clear, up-to-date coverage of three basic subtasks: active model abstraction, model application, and integration. It is the only textbook to offer a thorough discussion of active model abstraction.

Autonomous Learning Systems

Autonomous Learning Systems

Author: Plamen P. Angelov

Publisher: John Wiley & Sons

Published: 2013-01-01

Total Pages: 273

ISBN-13: 9781118481899

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Book Synopsis Autonomous Learning Systems by : Plamen P. Angelov

Download or read book Autonomous Learning Systems written by Plamen P. Angelov and published by John Wiley & Sons. This book was released on 2013-01-01 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Intelligent Autonomous Systems

Intelligent Autonomous Systems

Author: Dilip Kumar Pratihar

Publisher: Springer Science & Business Media

Published: 2010-02-24

Total Pages: 269

ISBN-13: 3642116752

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This research book contains a sample of most recent research in the area of intelligent autonomous systems. The contributions include: General aspects of intelligent autonomous systems Design of intelligent autonomous robots Biped robots Robot for stair-case navigation Ensemble learning for multi-source information fusion Intelligent autonomous systems in psychiatry Condition monitoring of internal combustion engine Security management of an enterprise network High dimensional neural nets and applications This book is directed to engineers, scientists, professor and the undergraduate/postgraduate students who wish to explore this field further.


Book Synopsis Intelligent Autonomous Systems by : Dilip Kumar Pratihar

Download or read book Intelligent Autonomous Systems written by Dilip Kumar Pratihar and published by Springer Science & Business Media. This book was released on 2010-02-24 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research book contains a sample of most recent research in the area of intelligent autonomous systems. The contributions include: General aspects of intelligent autonomous systems Design of intelligent autonomous robots Biped robots Robot for stair-case navigation Ensemble learning for multi-source information fusion Intelligent autonomous systems in psychiatry Condition monitoring of internal combustion engine Security management of an enterprise network High dimensional neural nets and applications This book is directed to engineers, scientists, professor and the undergraduate/postgraduate students who wish to explore this field further.

Autonomous Learning in the Workplace

Autonomous Learning in the Workplace

Author: Jill E. Ellingson

Publisher: Taylor & Francis

Published: 2017-03-27

Total Pages: 336

ISBN-13: 1317378261

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Traditionally, organizations and researchers have focused on learning that occurs through formal training and development programs. However, the realities of today’s workplace suggest that it is difficult, if not impossible, for organizations to rely mainly on formal programs for developing human capital. This volume offers a broad-based treatment of autonomous learning to advance our understanding of learner-driven approaches and how organizations can support them. Contributors in industrial/organizational psychology, management, education, and entrepreneurship bring theoretical perspectives to help us understand autonomous learning and its consequences for individuals and organizations. Chapters consider informal learning, self-directed learning, learning from job challenges, mentoring, Massive Open Online Courses (MOOCs), organizational communities of practice, self-regulation, the role of feedback and errors, and how to capture value from autonomous learning. This book will appeal to scholars, researchers, and practitioners in psychology, management, training and development, and educational psychology.


Book Synopsis Autonomous Learning in the Workplace by : Jill E. Ellingson

Download or read book Autonomous Learning in the Workplace written by Jill E. Ellingson and published by Taylor & Francis. This book was released on 2017-03-27 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditionally, organizations and researchers have focused on learning that occurs through formal training and development programs. However, the realities of today’s workplace suggest that it is difficult, if not impossible, for organizations to rely mainly on formal programs for developing human capital. This volume offers a broad-based treatment of autonomous learning to advance our understanding of learner-driven approaches and how organizations can support them. Contributors in industrial/organizational psychology, management, education, and entrepreneurship bring theoretical perspectives to help us understand autonomous learning and its consequences for individuals and organizations. Chapters consider informal learning, self-directed learning, learning from job challenges, mentoring, Massive Open Online Courses (MOOCs), organizational communities of practice, self-regulation, the role of feedback and errors, and how to capture value from autonomous learning. This book will appeal to scholars, researchers, and practitioners in psychology, management, training and development, and educational psychology.

Autonomous Learner Model Resource Book

Autonomous Learner Model Resource Book

Author: George Betts

Publisher: Routledge

Published: 2021-09-03

Total Pages: 291

ISBN-13: 1000490246

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Autonomous Learner Model Resource Book includes activities and strategies to support the development of autonomous learners. More than 40 activities are included, all geared to the emotional, social, cognitive, and physical development of students. Teachers may use these activities and strategies with the entire class, small groups, or with individuals who are ready to be independent, self-directed, lifelong learners. These learners have the passions, abilities, skills, and attitudes to go beyond the regular curriculum and take control of their own educational pathways. Field-tested strategies and activities in the book include Find Someone Who, Teacher and Learner Questionnaires, Lifelong Notebook, Time Capsule, and Night of the Notables.


Book Synopsis Autonomous Learner Model Resource Book by : George Betts

Download or read book Autonomous Learner Model Resource Book written by George Betts and published by Routledge. This book was released on 2021-09-03 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous Learner Model Resource Book includes activities and strategies to support the development of autonomous learners. More than 40 activities are included, all geared to the emotional, social, cognitive, and physical development of students. Teachers may use these activities and strategies with the entire class, small groups, or with individuals who are ready to be independent, self-directed, lifelong learners. These learners have the passions, abilities, skills, and attitudes to go beyond the regular curriculum and take control of their own educational pathways. Field-tested strategies and activities in the book include Find Someone Who, Teacher and Learner Questionnaires, Lifelong Notebook, Time Capsule, and Night of the Notables.

Designing Autonomous AI

Designing Autonomous AI

Author: Kence Anderson

Publisher: "O'Reilly Media, Inc."

Published: 2022-06-14

Total Pages: 253

ISBN-13: 1098110706

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Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs


Book Synopsis Designing Autonomous AI by : Kence Anderson

Download or read book Designing Autonomous AI written by Kence Anderson and published by "O'Reilly Media, Inc.". This book was released on 2022-06-14 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs

Learning for Adaptive and Reactive Robot Control

Learning for Adaptive and Reactive Robot Control

Author: Aude Billard

Publisher: MIT Press

Published: 2022-02-08

Total Pages: 425

ISBN-13: 0262367017

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Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.


Book Synopsis Learning for Adaptive and Reactive Robot Control by : Aude Billard

Download or read book Learning for Adaptive and Reactive Robot Control written by Aude Billard and published by MIT Press. This book was released on 2022-02-08 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.

Toward Learning Robots

Toward Learning Robots

Author: Walter Van de Velde

Publisher: MIT Press

Published: 1993

Total Pages: 182

ISBN-13: 9780262720175

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The contributions in Toward Learning Robots address the question of how a robot can be designed to acquire autonomously whatever it needs to realize adequate behavior in a complex environment. In-depth discussions of issues, techniques, and experiments in machine learning focus on improving ease of programming and enhancing robustness in unpredictable and changing environments, given limitations of time and resources available to researchers. The authors show practical progress toward a useful set of abstractions and techniques to describe and automate various aspects of learning in autonomous systems. The close interaction of such a system with the world reveals opportunities for new architectures and learning scenarios and for grounding symbolic representations, though such thorny problems as noise, choice of language, abstraction level of representation, and operationality have to be faced head-on. Contents Introduction: Toward Learning Robots * Learning Reliable Manipulation Strategies without Initial Physical Models * Learning by an Autonomous Agent in the Pushing Domain * A Cost-Sensitive Machine Learning Method for the Approach and Recognize Task * A Robot Exploration and Mapping Strategy Based on a Semantic Hierarchy of Spatial Representations * Understanding Object Motion: Recognition, Learning and Spatiotemporal Reasoning * Learning How to Plan * Robo-Soar: An Integration of External Interaction, Planning, and Learning Using Soar * Foundations of Learning in Autonomous Agents * Prior Knowledge and Autonomous Learning


Book Synopsis Toward Learning Robots by : Walter Van de Velde

Download or read book Toward Learning Robots written by Walter Van de Velde and published by MIT Press. This book was released on 1993 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributions in Toward Learning Robots address the question of how a robot can be designed to acquire autonomously whatever it needs to realize adequate behavior in a complex environment. In-depth discussions of issues, techniques, and experiments in machine learning focus on improving ease of programming and enhancing robustness in unpredictable and changing environments, given limitations of time and resources available to researchers. The authors show practical progress toward a useful set of abstractions and techniques to describe and automate various aspects of learning in autonomous systems. The close interaction of such a system with the world reveals opportunities for new architectures and learning scenarios and for grounding symbolic representations, though such thorny problems as noise, choice of language, abstraction level of representation, and operationality have to be faced head-on. Contents Introduction: Toward Learning Robots * Learning Reliable Manipulation Strategies without Initial Physical Models * Learning by an Autonomous Agent in the Pushing Domain * A Cost-Sensitive Machine Learning Method for the Approach and Recognize Task * A Robot Exploration and Mapping Strategy Based on a Semantic Hierarchy of Spatial Representations * Understanding Object Motion: Recognition, Learning and Spatiotemporal Reasoning * Learning How to Plan * Robo-Soar: An Integration of External Interaction, Planning, and Learning Using Soar * Foundations of Learning in Autonomous Agents * Prior Knowledge and Autonomous Learning

Learner Autonomy and Web 2.0

Learner Autonomy and Web 2.0

Author: Marco Cappellini

Publisher: Equinox Publishing (UK)

Published: 2017

Total Pages:

ISBN-13: 9781781795989

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This volume explores tensions between the "classical" definitions of learner autonomy and the learning dynamics observed in specific online contexts. Some of the contributions argue for the emergence of actual new forms of autonomy, others consider that this is merely a case of "old wine in new bottles". In this volume, autonomy is seen as emerging and developing in a complex relationship with L2 proficiency and other competencies. The volume takes an expansive view of what is meant by Web 2.0 and, as a result, a wide diversity of environments is featured, ranging from adaptive learning systems, through mobile apps, to social networking sites and - almost inevitably - MOOCs. Paradoxically, autonomy is seen to flourish in some quite restricted contexts, while in less constrained environments learners experience difficulty in dealing with a requirement to self-regulate.Individual chapters run the gamut of age groups, learning activities and online environments. The stage for all of them is set by an exchange in which David Little and Steve Thorne discuss the evolution of the concept of language learner autonomy, from its origins in the era of self-access resource centres to its more recent instantiations in online (and offline) learning communities. Subsequent contributors include an exploration how autonomy can be exercised even within the constraints of adaptive learning systems, a discussion of the metacognitive operations engaged in by autonomous adult learners in a French/Australian teletandem exchange, a look at an ecological paradigm of autonomy to conceptualise its emergence in relation to the use of mobile apps by primary- and secondary-level language learners in Canada, a study of how learner autonomy with a markedly social and empathic dimension drives collaboration in a Facebook-based collaborative writing project, an analysis of the difficulties encountered by a group of trainee language teachers in engaging with a range of language MOOCs and finally a study of how autonomy is experienced by advanced learners of English with a preference for online informal learning based on gaming and streamed video.


Book Synopsis Learner Autonomy and Web 2.0 by : Marco Cappellini

Download or read book Learner Autonomy and Web 2.0 written by Marco Cappellini and published by Equinox Publishing (UK). This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores tensions between the "classical" definitions of learner autonomy and the learning dynamics observed in specific online contexts. Some of the contributions argue for the emergence of actual new forms of autonomy, others consider that this is merely a case of "old wine in new bottles". In this volume, autonomy is seen as emerging and developing in a complex relationship with L2 proficiency and other competencies. The volume takes an expansive view of what is meant by Web 2.0 and, as a result, a wide diversity of environments is featured, ranging from adaptive learning systems, through mobile apps, to social networking sites and - almost inevitably - MOOCs. Paradoxically, autonomy is seen to flourish in some quite restricted contexts, while in less constrained environments learners experience difficulty in dealing with a requirement to self-regulate.Individual chapters run the gamut of age groups, learning activities and online environments. The stage for all of them is set by an exchange in which David Little and Steve Thorne discuss the evolution of the concept of language learner autonomy, from its origins in the era of self-access resource centres to its more recent instantiations in online (and offline) learning communities. Subsequent contributors include an exploration how autonomy can be exercised even within the constraints of adaptive learning systems, a discussion of the metacognitive operations engaged in by autonomous adult learners in a French/Australian teletandem exchange, a look at an ecological paradigm of autonomy to conceptualise its emergence in relation to the use of mobile apps by primary- and secondary-level language learners in Canada, a study of how learner autonomy with a markedly social and empathic dimension drives collaboration in a Facebook-based collaborative writing project, an analysis of the difficulties encountered by a group of trainee language teachers in engaging with a range of language MOOCs and finally a study of how autonomy is experienced by advanced learners of English with a preference for online informal learning based on gaming and streamed video.