Download or read book Adaptive Behavior and Learning written by J. E. R. Staddon and published by Cambridge University Press. This book was released on 2016-03-10 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summarizes the current state of both theoretical and experimental knowledge about learning in animals.

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello and published by Butterworth-Heinemann. This book was released on 2018-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Download or read book Innovative Trends in Flipped Teaching and Adaptive Learning written by Sein-Echaluce, María Luisa and published by IGI Global. This book was released on 2019-05-15 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding new educational innovations is essential for the improvement of the training and learning process. In order to effectively implement these new tools in the classroom, teachers and trainers need access to real-life cases in which these methods were successfully used. Innovative Trends in Flipped Teaching and Adaptive Learning is a critical scholarly resource that examines current advances in educational innovation and presents cases that allow for the improvement of personalized and active learning. Featuring a wide range of topics such as higher education, teacher education, and learning strategies, this book is ideal for educators, instructional designers, academicians, researchers, and students.

Download or read book Designing Adaptive and Personalized Learning Environments written by Kinshuk and published by Routledge. This book was released on 2016-03-31 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing Adaptive and Personalized Learning Environments provides a theoretically-based yet practical guide to systematic design processes for learning environments that provide automatic customization of learning and instruction. The book consists of four main sections: In "Introduction and Overview," the concepts of adaptivity and personalization are introduced and explored in detail. In "Theoretical Perspectives with Example Applications," various theoretical concepts underlying adaptive and personalized learning are discussed, including cognitive profiling, content-based adaptivity, exploration-based adaptivity, and mobile and ubiquitous settings. In "Practical Perspectives with Example Applications," the implementation process for adaptive and personalized learning environments is described, followed by application in various contexts. In "Validation and Future Trends," various evaluation techniques for validating the efficiency and efficacy of adaptive and personalized learning systems are discussed. This final section concludes with a discussion of emerging trends in adaptive and personalized learning research. Based on cutting-edge research, Designing Adaptive and Personalized Learning Environments is appropriate as a primary textbook for both undergraduate and graduate courses focused on the design of learning systems, and as a secondary textbook for a variety of courses in programs such as educational technology, instructional design, learning sciences, digital literacy, computer based systems, and STEM content fields.

Download or read book Transactional Distance and Adaptive Learning written by Farhad Saba and published by Routledge. This book was released on 2017-10-16 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transactional Distance and Adaptive Learning takes a fresh look at one of the pioneering educational theories that accommodates the impact of information and communications technologies in learning. The theory of transactional distance (TTD) provides a distinct analytical and planning foundation for educators to conduct an overarching inquiry into transitioning from mass instructional and management systems in higher education to dynamic and transformational futures that focus on each individual learner. Based on the TTD, this pragmatic approach offers instructors, administrators, students, and other stakeholders a comprehensive planning method to assess the current state of their instructional, learning, and management practices and to develop alternative models to prescribe future improvements in their institution. This complex, self-organized, and adaptive method includes current and emergent properties of: hardware, software, and telecommunications systems that allow faculty, students, and administrators to communicate; instructional and curriculum systems that provide teaching and learning environments for faculty and students; and management, societal, and global systems that influence how institutions are supported, funded, and managed.

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.

Download or read book Adaptive and Learning Systems written by Kumpati S. Narendra and published by Springer Science & Business Media. This book was released on 2013-11-22 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers a glimpse of the status of research in adaptive and learning systems in 1985. In recent years these areas have spawned a multiplicity of ideas so rapidly that the average research worker or practicing engineer is overwhelmed by the flood of information. The Yale Workshop on Applications of Adaptive Systems Theory was organized in 1979 to provide a brief respite from this deluge, wherein critical issues may be examined in a calm and collegial environment. The fourth of the series having been held in May 1985, it has now become well established as a biennial forum for the lively exchange of ideas in the ever changing domain of adaptive systems. The scope of this book is broad and ranges from theoretical investigations to practical applications. It includes twenty eight papers by leaders in the field, selected from the Pro ceedings of the Fourth Yale Workshop and divided into five sections. I have provided a brief introduction to each section so that it can be read as a self-contained unit. The first section, devoted to adaptive control theory, suggests the intensity of activity in the field and reveals signs of convergence towards some common themes by workers with rather different moti vation. Preliminary results concerning the reduced order model problem are dramatically changing the way we view the field and bringing it closer to other areas such as robust linear control where major advances have been recently reported.

Download or read book Personalization and Collaboration in Adaptive E Learning written by Tadlaoui, Mouenis Anouar and published by IGI Global. This book was released on 2019-12-13 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of e-learning, adaptive systems are more specialized and focus on the adaptation of learning content and presentation of this content. An adaptive system focuses on how knowledge is learned and pays attention to the activities, cognitive structures, and context of the learning material. The adaptive term refers to the automatic adaptation of the system to the learner. The needs of the learner are borne by the system itself. The learner did not ask to change the parameters of the system to his own needs; it is rather the needs of the learner that will be supposed by the system. The system adapts according to this necessity. Personalization and Collaboration in Adaptive E-Learning is an essential reference book that aims to describe the specific steps in designing a scenario for a collaborative learning activity in the particular context of personalization in adaptive systems and the key decisions that need to be made by the teacher-learner. By applying theoretical and practical aspects of personalization in adaptive systems and applications within education, this collection features coverage on a broad range of topics that include adaptive teaching, personalized learning, and instructional design. This book is ideally designed for instructional designers, curriculum developers, educational software developers, IT specialists, educational administrators, professionals, professors, researchers, and students seeking current research on comparative studies and the pedagogical issues of personalized and collaborative learning.

Download or read book The Master Adaptive Learner written by William Cutrer and published by Elsevier Health Sciences. This book was released on 2019-09-29 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tomorrow's best physicians will be those who continually learn, adjust, and innovate as new information and best practices evolve, reflecting adaptive expertise in response to practice challenges. As the first volume in the American Medical Association's MedEd Innovation Series, The Master Adaptive Learner is an instructor-focused guide covering models for how to train and teach future clinicians who need to develop these adaptive skills and utilize them throughout their careers. - Explains and clarifies the concept of a Master Adaptive Learner: a metacognitive approach to learning based on self-regulation that fosters the success and use of adaptive expertise in practice. - Contains both theoretical and practical material for instructors and administrators, including guidance on how to implement a Master Adaptive Learner approach in today's institutions. - Gives instructors the tools needed to empower students to become efficient and successful adaptive learners. - Helps medical faculty and instructors address gaps in physician training and prepare new doctors to practice effectively in 21st century healthcare systems. - One of the American Medical Association Change MedEd initiatives and innovations, written and edited by members of the ACE (Accelerating Change in Medical Education) Consortium – a unique, innovative collaborative that allows for the sharing and dissemination of groundbreaking ideas and projects.

Download or read book Adaptive Micro Learning written by Geng Sun (Researcher on educational technology) and published by World Scientific. This book was released on 2020 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Managing Cognitive Load in Adaptive Multimedia Learning written by Slava Kalyuga and published by IGI Global Snippet. This book was released on 2009 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in multimedia and computer-based learning has entered a new phase with a focus on adapting instruction to characteristics of individual learners.

Download or read book Learning Based Adaptive Control written by Mouhacine Benosman and published by Butterworth-Heinemann. This book was released on 2016-08-02 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. - Includes a good number of Mechatronics Examples of the techniques. - Compares and blends Model-free and Model-based learning algorithms. - Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

Download or read book Intelligent and Adaptive Educational Learning Systems written by Alejandro Peña-Ayala and published by Springer Science & Business Media. This book was released on 2012-08-10 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form. This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research. After a rigorous revision process twenty manuscripts were accepted and organized into four parts: Modeling, Content, Virtuality and Applications. This volume is of interest to researchers, practitioners, professors and postgraduate students aimed to update their knowledge and find out targets for future work in the field of artificial intelligence on education.

Download or read book Adaptive Learning and the Human Condition written by Jeffrey C. Levy and published by Routledge. This book was released on 2021-09-30 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning and the Human Condition provides a coherent and comprehensive introduction to the basic principles of classical (Pavlovian) and instrumental (Skinnerian) conditioning. When combined with observational learning and language, they are responsible for human accomplishment from the Stone Age to the digital age. This edition has been thoroughly updated throughout, relating adaptive learning principles to clinical applications as well as non-traditional topics such as parenting, moral development, and the helping professions. Defining learning as an adaptive process enables students to understand the need to review the basic animal research literature in classical and operant conditioning and consider how it applies to human beings in our everyday lives. Divided into four parts, this book covers historical research into psychology and adaptive learning, principles of adaptive learning (prediction and control), adaptive learning and the human condition, and behavior modification and the helping professions. The book showcases how an adaptive learning strategy can be practical, diagnostic, and prescriptive, making this an essential companion for psychology students and those enrolled in programs in professional schools and helping professions including psychiatry, special education, health psychology, and physical therapy.

Download or read book Adaptive Learning and the Human Condition written by Jeffrey C. Levy and published by Routledge. This book was released on 2015-10-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning and the Human Condition presents the basic principles of classical (Pavlovian) and instrumental (Skinnerian) conditioning in a more coherent and expansive manner than is the case in other textbooks. Learning is defined as an adaptive process through which individuals acquire the ability to predict, and where possible, control the environment. This overarching definition enables integration of traditional Pavlovian and Skinnerian principles and terminology and makes explicit why treatment of the learning process is essentially limited to these two historical research paradigms. Pavlov developed a methodology for studying animals under circumstances where they could predict, but not control, sequences of environmental events. Skinner studied animals under circumstances where their behavior had an effect upon environmental events. Observational learning and symbolic communication (i.e., spoken or written language) are incorporated as indirect learning processes through which individuals can acquire the ability to predict or control. This treatment creates a perspective within which it is possible to consider the fundamental nature of the learning process in understanding the human condition and in addressing significant individual and social concerns. Examples of applications and issues not included in similar textbooks include: The role of classical and instrumental conditioning in language acquisition The administration of rewards and punishers in Baumrind’s parental styles as related to Kohlberg’s stages of moral development Stone-Age hunter-gatherer and technologically-advanced cultures: How did we get from there to here? Self-control and self-actualization While covering traditional technical and theoretical issues, the book is written in a clear, engaging style. The narrative builds across chapters, culminating in the treatment of applications and societal concerns of import and interest to students and faculty alike. Upon completing this book, readers should be able to: explain the significance of human condition through adaptive learning; present the basic principles of classical and instrumental conditioning; and understand the significance of scientific research

Download or read book Advancing the Power of Learning Analytics and Big Data in Education written by Azevedo, Ana and published by IGI Global. This book was released on 2021-03-19 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term learning analytics is used in the context of the use of analytics in e-learning environments. Learning analytics is used to improve quality. It uses data about students and their activities to provide better understanding and to improve student learning. The use of learning management systems, where the activity of the students can be easily accessed, potentiated the use of learning analytics to understand their route during the learning process, help students be aware of their progress, and detect situations where students can give up the course before its completion, which is a growing problem in e-learning environments. Advancing the Power of Learning Analytics and Big Data in Education provides insights concerning the use of learning analytics, the role and impact of analytics on education, and how learning analytics are designed, employed, and assessed. The chapters will discuss factors affecting learning analytics such as human factors, geographical factors, technological factors, and ethical and legal factors. This book is ideal for teachers, administrators, teacher educators, practitioners, stakeholders, researchers, academicians, and students interested in the use of big data and learning analytics for improved student success and educational environments.