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Author : Fei Chen
Publisher : Frontiers Media SA
ISBN 13 : 2832511910
Total Pages : 248 pages
Book Rating : 4.8/5 (325 download)
Download or read book Neurorobotics explores machine learning written by Fei Chen and published by Frontiers Media SA. This book was released on 2023-01-20 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Tiffany J. Hwu
Publisher : MIT Press
ISBN 13 : 0262047063
Total Pages : 245 pages
Book Rating : 4.2/5 (62 download)
Download or read book Neurorobotics written by Tiffany J. Hwu and published by MIT Press. This book was released on 2022-11-29 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to neurorobotics that presents approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. Neurorobotics is an interdisciplinary field that draws on artificial intelligence, cognitive sciences, computer science, engineering, psychology, neuroscience, and robotics. Because the brain is closely coupled to the body and situated in the environment, neurorobots—autonomous systems modeled after some aspect of the brain—offer a powerful tool for studying neural function and may also be a means for developing autonomous systems with intelligence that rivals that of biological organisms. This textbook introduces approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. It is written for anyone interested in learning about this topic and can be used in cognitive robotics courses for students in psychology, cognitive science, and computer science. Neurorobotics covers the background and foundations of the field, with information on early neurorobots, relevant principles of neuroscience, learning rules and mechanisms, and reinforcement learning and prediction; neurorobot design principles grounded in neuroscience and principles of neuroscience research; and examples of neurorobots for navigation, developmental robotics, and social robots, presented with the cognitive science and neuroscience background that inspired them. A supplementary website offers videos, robot simulations, and links to software repositories with neurorobot examples.
Author : Ajith Abraham
Publisher : Academic Press
ISBN 13 : 0323902782
Total Pages : 434 pages
Book Rating : 4.3/5 (239 download)
Download or read book Artificial Intelligence for Neurological Disorders written by Ajith Abraham and published by Academic Press. This book was released on 2022-09-23 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. Discusses various AI and ML methods to apply for neurological research Explores Deep Learning techniques for brain MRI images Covers AI techniques for the early detection of neurological diseases and seizure prediction Examines cognitive therapies using AI and Deep Learning methods
Author : Sonia Chernova
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1627052003
Total Pages : 123 pages
Book Rating : 4.6/5 (27 download)
Download or read book Robot Learning from Human Teachers written by Sonia Chernova and published by Morgan & Claypool Publishers. This book was released on 2014-04-01 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
Author : Judy A. Franklin
Publisher : Springer Science & Business Media
ISBN 13 : 9780792397458
Total Pages : 226 pages
Book Rating : 4.3/5 (974 download)
Download or read book Recent Advances in Robot Learning written by Judy A. Franklin and published by Springer Science & Business Media. This book was released on 1996-06-30 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).
Author : Jose De Jesus Rubio
Publisher : Frontiers Media SA
ISBN 13 : 2889667685
Total Pages : 149 pages
Book Rating : 4.8/5 (896 download)
Download or read book Advances in Robots Trajectories Learning via Fast Neural Networks written by Jose De Jesus Rubio and published by Frontiers Media SA. This book was released on 2021-05-14 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : D. Jude Hemanth
Publisher : Elsevier
ISBN 13 : 0443137722
Total Pages : 302 pages
Book Rating : 4.4/5 (431 download)
Download or read book Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications written by D. Jude Hemanth and published by Elsevier. This book was released on 2023-11-17 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications explores the different possibilities of providing AI based neuro-rehabilitation methods to treat neurological disorders. The book provides in-depth knowledge on the challenges and solutions associated with the different varieties of neuro-rehabilitation through the inclusion of case studies and real-time scenarios in different geographical locations. Beginning with an overview of neuro-rehabilitation applications, the book discusses the role of machine learning methods in brain function grading for adults with Mild Cognitive Impairment, Brain Computer Interface for post-stroke patients, developing assistive devices for paralytic patients, and cognitive treatment for spinal cord injuries. Topics also include AI-based video games to improve the brain performances in children with autism and ADHD, deep learning approaches and magnetoencephalography data for limb movement, EEG signal analysis, smart sensors, and the application of robotic concepts for gait control.
Author : Florian Röhrbein
Publisher : Frontiers Media SA
ISBN 13 : 2832505902
Total Pages : 165 pages
Book Rating : 4.8/5 (325 download)
Download or read book Insights in Neurorobotics: 2021 written by Florian Röhrbein and published by Frontiers Media SA. This book was released on 2022-11-16 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Walter Van de Velde
Publisher : MIT Press
ISBN 13 : 9780262720175
Total Pages : 182 pages
Book Rating : 4.7/5 (21 download)
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
Author : Miguel Angel Cazorla Quevedo
Publisher : MDPI
ISBN 13 : 3039363387
Total Pages : 210 pages
Book Rating : 4.0/5 (393 download)
Download or read book Machine Learning Techniques for Assistive Robotics written by Miguel Angel Cazorla Quevedo and published by MDPI. This book was released on 2020-12-10 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assistive robots are categorized as robots that share their area of work and interact with humans. Their main goals are to help, assist, and monitor humans, especially people with disabilities. To achieve these goals, it is necessary that these robots possess a series of characteristics, namely the abilities to perceive their environment from their sensors and act consequently, to interact with people in a multimodal manner, and to navigate and make decisions autonomously. This complexity demands computationally expensive algorithms to be performed in real time. The advent of high-end embedded processors has enabled several such algorithms to be processed concurrently and in real time. All these capabilities involve, to a greater or less extent, the use of machine learning techniques. In particular, in the last few years, new deep learning techniques have enabled a very important qualitative leap in different problems related to perception, navigation, and human understanding. In this Special Issue, several works are presented involving the use of machine learning techniques for assistive technologies, in particular for assistive robots.
Author : Kevin A. Gluck
Publisher : MIT Press
ISBN 13 : 026203882X
Total Pages : 355 pages
Book Rating : 4.2/5 (62 download)
Download or read book Interactive Task Learning written by Kevin A. Gluck and published by MIT Press. This book was released on 2019-09-10 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experts from a range of disciplines explore how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. Humans are not limited to a fixed set of innate or preprogrammed tasks. We learn quickly through language and other forms of natural interaction, and we improve our performance and teach others what we have learned. Understanding the mechanisms that underlie the acquisition of new tasks through natural interaction is an ongoing challenge. Advances in artificial intelligence, cognitive science, and robotics are leading us to future systems with human-like capabilities. A huge gap exists, however, between the highly specialized niche capabilities of current machine learning systems and the generality, flexibility, and in situ robustness of human instruction and learning. Drawing on expertise from multiple disciplines, this Strüngmann Forum Report explores how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. The contributors consider functional knowledge requirements, the ontology of interactive task learning, and the representation of task knowledge at multiple levels of abstraction. They explore natural forms of interactions among humans as well as the use of interaction to teach robots and software agents new tasks in complex, dynamic environments. They discuss research challenges and opportunities, including ethical considerations, and make proposals to further understanding of interactive task learning and create new capabilities in assistive robotics, healthcare, education, training, and gaming. Contributors Tony Belpaeme, Katrien Beuls, Maya Cakmak, Joyce Y. Chai, Franklin Chang, Ropafadzo Denga, Marc Destefano, Mark d'Inverno, Kenneth D. Forbus, Simon Garrod, Kevin A. Gluck, Wayne D. Gray, James Kirk, Kenneth R. Koedinger, Parisa Kordjamshidi, John E. Laird, Christian Lebiere, Stephen C. Levinson, Elena Lieven, John K. Lindstedt, Aaron Mininger, Tom Mitchell, Shiwali Mohan, Ana Paiva, Katerina Pastra, Peter Pirolli, Roussell Rahman, Charles Rich, Katharina J. Rohlfing, Paul S. Rosenbloom, Nele Russwinkel, Dario D. Salvucci, Matthew-Donald D. Sangster, Matthias Scheutz, Julie A. Shah, Candace L. Sidner, Catherine Sibert, Michael Spranger, Luc Steels, Suzanne Stevenson, Terrence C. Stewart, Arthur Still, Andrea Stocco, Niels Taatgen, Andrea L. Thomaz, J. Gregory Trafton, Han L. J. van der Maas, Paul Van Eecke, Kurt VanLehn, Anna-Lisa Vollmer, Janet Wiles, Robert E. Wray III, Matthew Yee-King
Author : Victor E. Staartjes
Publisher : Springer Nature
ISBN 13 : 303085292X
Total Pages : 343 pages
Book Rating : 4.0/5 (38 download)
Download or read book Machine Learning in Clinical Neuroscience written by Victor E. Staartjes and published by Springer Nature. This book was released on 2021-12-03 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.
Author : Kamal Malik
Publisher : CRC Press
ISBN 13 : 1000994147
Total Pages : 243 pages
Book Rating : 4.0/5 (9 download)
Download or read book Computational Techniques in Neuroscience written by Kamal Malik and published by CRC Press. This book was released on 2023-11-14 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Author : Tiffany J. Hwu
Publisher : MIT Press
ISBN 13 : 0262370530
Total Pages : 245 pages
Book Rating : 4.2/5 (623 download)
Download or read book Neurorobotics written by Tiffany J. Hwu and published by MIT Press. This book was released on 2022-11-29 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to neurorobotics that presents approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. Neurorobotics is an interdisciplinary field that draws on artificial intelligence, cognitive sciences, computer science, engineering, psychology, neuroscience, and robotics. Because the brain is closely coupled to the body and situated in the environment, neurorobots—autonomous systems modeled after some aspect of the brain—offer a powerful tool for studying neural function and may also be a means for developing autonomous systems with intelligence that rivals that of biological organisms. This textbook introduces approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. It is written for anyone interested in learning about this topic and can be used in cognitive robotics courses for students in psychology, cognitive science, and computer science. Neurorobotics covers the background and foundations of the field, with information on early neurorobots, relevant principles of neuroscience, learning rules and mechanisms, and reinforcement learning and prediction; neurorobot design principles grounded in neuroscience and principles of neuroscience research; and examples of neurorobots for navigation, developmental robotics, and social robots, presented with the cognitive science and neuroscience background that inspired them. A supplementary website offers videos, robot simulations, and links to software repositories with neurorobot examples.
Author : Anitha S. Pillai
Publisher :
ISBN 13 : 9781003264767
Total Pages : 0 pages
Book Rating : 4.2/5 (647 download)
Download or read book Machine Learning and Deep Learning in Neuroimaging Data Analysis written by Anitha S. Pillai and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Machine Learning (ML) and Deep Learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together both AI experts as well as medical practitioners, chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research"--
Author : Teresa Lopez-Soto
Publisher : Springer Nature
ISBN 13 : 3031467426
Total Pages : 741 pages
Book Rating : 4.0/5 (314 download)
Download or read book The Theory of Mind Under Scrutiny written by Teresa Lopez-Soto and published by Springer Nature. This book was released on 2024-01-01 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a call to expand and diversify our approach to the study of the human mind in relation to the Theory of Mind. It proposes that it is necessary to combine cross-disciplinary methods to arrive at a more complete understanding of how our minds work. Seeking to expand the discussion surrounding the Theory of Mind beyond the field of psychology, and its focus on our capacity to ascribe mental states to other people, this volume collects evidence and research to point to a more holistic understanding of our own minds, the minds of others, behavior, language, and reasoning. This book therefore illuminates the conceptual intricacy underlying the Theory of Mind. It posits that a wide scope is necessary to make a breakthrough in scientific research towards a full understanding of the nature, function, and development of our capacity to converge on biological processes of the brain towards consciousness, emotion, awareness, and cognition. The volume presents methods, results, critiques, and models intended to provoke debates in various academic disciplines. It is of interest to scholars working in psychology, neuroscience, philosophy of mind, and artificial intelligence.
Author : Jeremy Wyatt
Publisher : Springer
ISBN 13 : 3540400443
Total Pages : 173 pages
Book Rating : 4.5/5 (44 download)
Download or read book Advances in Robot Learning written by Jeremy Wyatt and published by Springer. This book was released on 2003-06-29 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 8th European Workshop on Learning Robots, EWLR'99, held in Lausanne, Switzerland in September 1999.The seven revised full workshop papers presented were carefully reviewed and selected for inclusion in the book. Also included are two invited full papers. Among the topics addressed are map building for robot navigation, multi-task reinforcement learning, neural network approaches, example-based learning, situated agents, planning maps for mobile robots, path finding, autonomous robots, and biologically inspired approaches.
