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Author: John Demiris
Publisher: World Scientific
ISBN: 9810243200
Category : Computers
Languages : en
Pages : 220
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Book Description
Annotation Robots are being used in increasingly complicated and demanding tasks, often in environments that are complex or even hostile. Underwater, space and volcano exploration are just some of the activities that robots are taking part in, mainly because the environments that are being explored are dangerous for humans. Robots can also inhabit dynamic environments, for example to operate among humans, not just in factories, but also taking on more active roles. Recently, for instance, they have made their way into the home entertainment market. Given the variety of situations that robots will be placed in, learning becomes increasingly important. Robot learning is essentially about equipping robots with the capacity to improve their behaviour over time, based on their incoming experiences. The papers in this volume present a variety of techniques. Each paper provides a mini-introduction to a subfield of robot learning. Some also give a fine introduction to the field of robot learning as a whole. Thereis one unifying aspect to the work reported in the book, namely its interdisciplinary nature, especially in the combination of robotics, computer science and biology. This approach has two important benefits: first, the study of learning in biological systems can provide robot learning scientists and engineers with valuable insights into learning mechanisms of proven functionality and versatility; second, computational models of learning in biological systems, and their implementation in simulated agents and robots, can provide researchers of biological systems with a powerful platform for the development and testing of learning theories.
Author: John Demiris
Publisher: World Scientific
ISBN: 9810243200
Category : Computers
Languages : en
Pages : 220
Get Book
Book Description
Annotation Robots are being used in increasingly complicated and demanding tasks, often in environments that are complex or even hostile. Underwater, space and volcano exploration are just some of the activities that robots are taking part in, mainly because the environments that are being explored are dangerous for humans. Robots can also inhabit dynamic environments, for example to operate among humans, not just in factories, but also taking on more active roles. Recently, for instance, they have made their way into the home entertainment market. Given the variety of situations that robots will be placed in, learning becomes increasingly important. Robot learning is essentially about equipping robots with the capacity to improve their behaviour over time, based on their incoming experiences. The papers in this volume present a variety of techniques. Each paper provides a mini-introduction to a subfield of robot learning. Some also give a fine introduction to the field of robot learning as a whole. Thereis one unifying aspect to the work reported in the book, namely its interdisciplinary nature, especially in the combination of robotics, computer science and biology. This approach has two important benefits: first, the study of learning in biological systems can provide robot learning scientists and engineers with valuable insights into learning mechanisms of proven functionality and versatility; second, computational models of learning in biological systems, and their implementation in simulated agents and robots, can provide researchers of biological systems with a powerful platform for the development and testing of learning theories.
Author: J Demiris
Publisher: World Scientific
ISBN: 9814492973
Category : Technology & Engineering
Languages : en
Pages : 220
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Book Description
Robots are being used in increasingly complicated and demanding tasks, often in environments that are complex or even hostile. Underwater, space and volcano exploration are just some of the activities that robots are taking part in, mainly because the environments that are being explored are dangerous for humans. Robots can also inhabit dynamic environments, for example to operate among humans, not just in factories, but also taking on more active roles. Recently, for instance, they have made their way into the home entertainment market. Given the variety of situations that robots will be placed in, learning becomes increasingly important. Robot learning is essentially about equipping robots with the capacity to improve their behaviour over time, based on their incoming experiences. The papers in this volume present a variety of techniques. Each paper provides a mini-introduction to a subfield of robot learning. Some also give a fine introduction to the field of robot learning as a whole. There is one unifying aspect to the work reported in the book, namely its interdisciplinary nature, especially in the combination of robotics, computer science and biology. This approach has two important benefits: first, the study of learning in biological systems can provide robot learning scientists and engineers with valuable insights into learning mechanisms of proven functionality and versatility; second, computational models of learning in biological systems, and their implementation in simulated agents and robots, can provide researchers of biological systems with a powerful platform for the development and testing of learning theories. Contents:Interdisciplinary Approaches to Robot Learning: Introduction (J Demiris & A Birk)Bootstrapping the Developmental Process: The Filter Hypothesis (L Berthouze)Biomimetic Gaze Stabilization (T Shibata & S Schaal)Experiments and Models About Cognitive Map Learning for Motivated Navigation (P Gaussier et al.)Learning Selection of Action for Cortically-Inspired Robot Control (H Frezza-Buet & F Alexandre)Transferring Learned Knowledge in a Lifelong Learning Mobile Robot Agent (J O'Sullivan)Of Hummingbirds and Helicopters: An Algebraic Framework for Interdisciplinary Studies of Imitation and Its Applications (C Nehaniv & K Dautenhahn)Evolving Complex Visual Behaviours Using Genetic Programming and Shaping (S Perkins & G M Hayes)Preston: A System for the Evaluation of Behaviour Sequences (M Wilson) Readership: Researchers and graduate students in robotics and machine learning who are interested in interdisciplinary approaches to their fields. Keywords:Robotics;Learning, Interdisciplinary Approaches;Robot Learning;Robots;Adaptivity;Biologically Inspired Robotics
Author: Angelo Cangelosi
Publisher: MIT Press
ISBN: 0262028018
Category : Technology & Engineering
Languages : en
Pages : 427
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Book Description
A comprehensive overview of an interdisciplinary approach to robotics that takes direct inspiration from the developmental and learning phenomena observed in children's cognitive development. Developmental robotics is a collaborative and interdisciplinary approach to robotics that is directly inspired by the developmental principles and mechanisms observed in children's cognitive development. It builds on the idea that the robot, using a set of intrinsic developmental principles regulating the real-time interaction of its body, brain, and environment, can autonomously acquire an increasingly complex set of sensorimotor and mental capabilities. This volume, drawing on insights from psychology, computer science, linguistics, neuroscience, and robotics, offers the first comprehensive overview of a rapidly growing field. After providing some essential background information on robotics and developmental psychology, the book looks in detail at how developmental robotics models and experiments have attempted to realize a range of behavioral and cognitive capabilities. The examples in these chapters were chosen because of their direct correspondence with specific issues in child psychology research; each chapter begins with a concise and accessible overview of relevant empirical and theoretical findings in developmental psychology. The chapters cover intrinsic motivation and curiosity; motor development, examining both manipulation and locomotion; perceptual development, including face recognition and perception of space; social learning, emphasizing such phenomena as joint attention and cooperation; language, from phonetic babbling to syntactic processing; and abstract knowledge, including models of number learning and reasoning strategies. Boxed text offers technical and methodological details for both psychology and robotics experiments.
Author: William Frere Lawless
Publisher: Frontiers Media SA
ISBN: 283251930X
Category : Science
Languages : en
Pages : 220
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Book Description
Author: Wilfried Lepuschitz
Publisher: Springer
ISBN: 3319628755
Category : Technology & Engineering
Languages : en
Pages : 330
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Book Description
This proceedings volume highlights the latest achievements in research and development in educational robotics, which were presented at the 8th International Conference on Robotics in Education (RiE 2017) in Sofia, Bulgaria, from April 26 to 28, 2017. The content will appeal to both researchers and educators interested in methodologies for teaching robotics that confront learners with science, technology, engineering, arts and mathematics (STEAM) through the design, creation and programming of tangible artifacts, giving them the chance to create personally meaningful objects and address real-world societal needs. This also involves the introduction of technologies ranging from robotics controllers to virtual environments. In addition, the book presents evaluation results regarding the impact of robotics on students’ interests and competence development. The approaches discussed cover the whole educational range, from elementary school to the university level, in both formal as well as informal settings.
Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
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Book Description
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.
Author: Myint Swe Khine
Publisher: Springer
ISBN: 3319577867
Category : Science
Languages : en
Pages : 262
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Book Description
This book describes recent approaches in advancing STEM education with the use of robotics, innovative methods in integrating robotics in school subjects, engaging and stimulating students with robotics in classroom-based and out-of-school activities, and new ways of using robotics as an educational tool to provide diverse learning experiences. It addresses issues and challenges in generating enthusiasm among students and revamping curricula to provide application focused and hands-on approaches in learning . The book also provides effective strategies and emerging trends in using robotics, designing learning activities and how robotics impacts the students’ interests and achievements in STEM related subjects. The frontiers of education are progressing very rapidly. This volume brought together a collection of projects and ideas which help us keep track of where the frontiers are moving. This book ticks lots of contemporary boxes: STEM, robotics, coding, and computational thinking among them. Most educators interested in the STEM phenomena will find many ideas in this book which challenge, provide evidence and suggest solutions related to both pedagogy and content. Regular reference to 21st Century skills, achieved through active collaborative learning in authentic contexts, ensures the enduring usefulness of this volume. John Williams Professor of Education and Director of the STEM Education Research Group Curtin University, Perth, Australia
Author: Fady Alnajjar
Publisher: Routledge
ISBN: 1000388840
Category : Education
Languages : en
Pages : 238
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Book Description
Robots in Education is an accessible introduction to the use of robotics in formal learning, encompassing pedagogical and psychological theories as well as implementation in curricula. Today, a variety of communities across education are increasingly using robots as general classroom tutors, tools in STEM projects, and subjects of study. This volume explores how the unique physical and social-interactive capabilities of educational robots can generate bonds with students while freeing instructors to focus on their individualized approaches to teaching and learning. Authored by a uniquely interdisciplinary team of scholars, the book covers the basics of robotics and their supporting technologies; attitudes toward and ethical implications of robots in learning; research methods relevant to extending our knowledge of the field; and more.
Author: Norbert M. Seel
Publisher: Springer Science & Business Media
ISBN: 1441914277
Category : Education
Languages : en
Pages : 3643
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Book Description
Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
Author: Chrystopher L. Nehaniv
Publisher: Cambridge University Press
ISBN: 1139461958
Category : Psychology
Languages : en
Pages : 409
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Book Description
Mechanisms of imitation and social matching play a fundamental role in development, communication, interaction, learning and culture. Their investigation in different agents (animals, humans and robots) has significantly influenced our understanding of the nature and origins of social intelligence. Whilst such issues have traditionally been studied in areas such as psychology, biology and ethnology, it has become increasingly recognised that a 'constructive approach' towards imitation and social learning via the synthesis of artificial agents can provide important insights into mechanisms and create artefacts that can be instructed and taught by imitation, demonstration, and social interaction rather than by explicit programming. This book studies increasingly sophisticated models and mechanisms of social matching behaviour and marks an important step towards the development of an interdisciplinary research field, consolidating and providing a valuable reference for the increasing number of researchers in the field of imitation and social learning in robots, humans and animals.
