Download or read book Growing Adaptive Machines written by Taras Kowaliw and published by Springer. This book was released on 2014-06-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the desi gn of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines. This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning.
Download or read book Fungal Machines written by Andrew Adamatzky and published by Springer Nature. This book was released on 2023-10-23 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book explores fungi as sensors, electronic devices, and potential future computers, offering eco-friendly alternatives to traditional electronics. Fungi are ancient, widely distributed organisms ranging from microscopic single cells to massive mycelium spanning hectares. They possess senses similar to humans, detecting light, chemicals, gases, gravity, and electric fields. It covers fungal electrical activity, sensors, electronics, computing prototypes, and fungal language. Authored by leading experts from diverse fields, the book is accessible to readers of all backgrounds, from high-schoolers to professors. It reveals the remarkable potential of fungal machines while minimizing environmental impact.
Download or read book Self Adaptive Systems for Machine Intelligence written by Haibo He and published by John Wiley & Sons. This book was released on 2011-09-15 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.
Download or read book Adaptive Control Design and Analysis written by Gang Tao and published by John Wiley & Sons. This book was released on 2003-07-09 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one's understanding of adaptive control theory. Adaptive Control Design and Analysis features: Introduction to systems and control Stability, operator norms, and signal convergence Adaptive parameter estimation State feedback adaptive control designs Parametrization of state observers for adaptive control Unified continuous and discrete-time adaptive control L1+a robustness theory for adaptive systems Direct and indirect adaptive control designs Benchmark comparison study of adaptive control designs Multivariate adaptive control Nonlinear adaptive control Adaptive compensation of actuator nonlinearities End-of-chapter discussion, problems, and advanced topics As either a textbook or reference, this self-contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike.
Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Download or read book AN ADAPTIVE MACHINE COMPUTATION OF DEEP LEARNING written by Mr. Neeraj Sharma and published by SK Research Group of Companies. This book was released on 2023-02-02 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mr. Neeraj Sharma, Associate Professor, Department of Electrical Engineering, Vivekananda Global University, Sector 36, Sisyawas, NRI Road, Jagatpura, Jaipur-303012, Rajasthan, India. Mr. Sandeep Kumar Jain, Associate Professor, Department of Electrical Engineering, Vivekananda Global University, Sector 36, Sisyawas, NRI Road, Jagatpura, Jaipur-303012, Rajasthan, India. Mr. Manish Srivastava, Assistant Professor, Department of Electrical Engineering, Vivekananda Global University, Sector 36, Sisyawas, NRI Road, Jagatpura, Jaipur-303012, Rajasthan, India. Mr. Pradeep Kumar Jangid, Assistant Professor, Department of Electrical Engineering, Vivekananda Global University, Sector 36, Sisyawas, NRI Road, Jagatpura, Jaipur-303012, Rajasthan, India. Mr. Ganesh Kumar Kantak, Assistant Professor, Department of Mechanical Engineering, Vivekananda Global University, Sector 36, Sisyawas, NRI Road, Jagatpura, Jaipur-303012, Rajasthan, India.
Download or read book Applications of Artificial Intelligence and Machine Learning written by Ankur Choudhary and published by Springer Nature. This book was released on 2021-07-27 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications.
Download or read book Advances in Mechanism and Machine Science written by Tadeusz Uhl and published by Springer. This book was released on 2019-06-13 with total page 4248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 15th IFToMM World Congress, which was held in Krakow, Poland, from June 30 to July 4, 2019. Having been organized every four years since 1965, the Congress represents the world’s largest scientific event on mechanism and machine science (MMS). The contributions cover an extremely diverse range of topics, including biomechanical engineering, computational kinematics, design methodologies, dynamics of machinery, multibody dynamics, gearing and transmissions, history of MMS, linkage and mechanical controls, robotics and mechatronics, micro-mechanisms, reliability of machines and mechanisms, rotor dynamics, standardization of terminology, sustainable energy systems, transportation machinery, tribology and vibration. Selected by means of a rigorous international peer-review process, they highlight numerous exciting advances and ideas that will spur novel research directions and foster new multidisciplinary collaborations.
Download or read book Increasing the Quality of life for the Older Adult written by Susan Brhel and published by Goals Seminars and Consulta. This book was released on 2005 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive and Natural Computing Algorithms written by Bartlomiej Beliczynski and published by Springer. This book was released on 2007-07-03 with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set constitutes the refereed proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007. Coverage in the first volume includes evolutionary computation, genetic algorithms, and particle swarm optimization. The second volume covers neural networks, support vector machines, biomedical signal and image processing, biometrics, computer vision.
Download or read book An Adaptive Machine Computation of Deep Learning written by Dr. M. Kasthuri and published by Leilani Katie Publication. This book was released on 2024-02-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr. M. Kasthuri, Associate Professor, Department of Computer Science, Bishop Heber College (Autonomous), Tiruchirappalli, Tamil Nadu, India. Mrs.M. Kavitha, Assistant Professor, Department of Computer Applications, Bishop Heber College (Autonomous), Tiruchirappalli, Tamil Nadu, India.
Download or read book How to Grow a Robot written by Mark H. Lee and published by MIT Press. This book was released on 2020-05-26 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to develop robots that will be more like humans and less like computers, more social than machine-like, and more playful and less programmed. Most robots are not very friendly. They vacuum the rug, mow the lawn, dispose of bombs, even perform surgery—but they aren't good conversationalists. It's difficult to make eye contact. If the future promises more human-robot collaboration in both work and play, wouldn't it be better if the robots were less mechanical and more social? In How to Grow a Robot, Mark Lee explores how robots can be more human-like, friendly, and engaging. Developments in artificial intelligence—notably Deep Learning—are widely seen as the foundation on which our robot future will be built. These advances have already brought us self-driving cars and chess match–winning algorithms. But, Lee writes, we need robots that are perceptive, animated, and responsive—more like humans and less like computers, more social than machine-like, and more playful and less programmed. The way to achieve this, he argues, is to “grow” a robot so that it learns from experience—just as infants do. After describing “what's wrong with artificial intelligence” (one key shortcoming: it's not embodied), Lee presents a different approach to building human-like robots: developmental robotics, inspired by developmental psychology and its accounts of early infant behavior. He describes his own experiments with the iCub humanoid robot and its development from newborn helplessness to ability levels equal to a nine-month-old, explaining how the iCub learns from its own experiences. AI robots are designed to know humans as objects; developmental robots will learn empathy. Developmental robots, with an internal model of “self,” will be better interactive partners with humans. That is the kind of future technology we should work toward.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-18 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 Transportation Traffic Safety and Health Man and Machine written by Hans von Holst and published by Springer Science & Business Media. This book was released on 2000-07-11 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hans von Holst Royal Institute of Technology, WHO Collaborating Center, Sweden Ake Nygren Karolinska Institute, WHO Collaborating Center, Sweden Ake E. Andersson Institute for Futures Studies, Sweden n a recent study initiated by Harvard University, World Bank and I World Health Organization it was concluded that road injuries will be ranked from number 9 today to number 3 within the next two to three decades if authorities all over the world do not pay more attention to this significant problem. Injuries in traffic do not only concern the patient himself but also the relatives from an emotional point of view and the society from a socio economic point. Both emerging markets and industrial countries have significant experi ence of the events following a traffic accident. Much effort has been directed towards transportation of the victim from the scene of the accident to intensive care unit in the hospital. Simultaneously, the awareness of our knowledge about how these injuries should be prevented is striking. The focus of this second book of transportation, traffic safety and health is to further present some of the latest aspects in the area of mobility and its rela tion to planning of an optimal traffic safety with respect to our present knowl edge in the field. The volume contains a collection of contributions presented of scientists, clinicians and administrators at The Second International Conference on Transportation, Traffic Safety and Health, held in Brussels, Belgium, 1996.
Download or read book Machine Learning written by Yagang Zhang and published by BoD – Books on Demand. This book was released on 2010-02-01 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large amount of knowledge about machine learning and practice presented in the book, it is divided into three major parts: Introduction, Machine Learning Theory and Applications. Part I focuses on the introduction to machine learning. The author also attempts to promote a new design of thinking machines and development philosophy. Considering the growing complexity and serious difficulties of information processing in machine learning, in Part II of the book, the theoretical foundations of machine learning are considered, and they mainly include self-organizing maps (SOMs), clustering, artificial neural networks, nonlinear control, fuzzy system and knowledge-based system (KBS). Part III contains selected applications of various machine learning approaches, from flight delays, network intrusion, immune system, ship design to CT and RNA target prediction. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners.
Download or read book Probabilistic Machine Learning written by Kevin P. Murphy and published by MIT Press. This book was released on 2022-03-01 with total page 858 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Download or read book Encyclopedia of Evolutionary Biology written by and published by Academic Press. This book was released on 2016-04-14 with total page 2138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encyclopedia of Evolutionary Biology, Four Volume Set is the definitive go-to reference in the field of evolutionary biology. It provides a fully comprehensive review of the field in an easy to search structure. Under the collective leadership of fifteen distinguished section editors, it is comprised of articles written by leading experts in the field, providing a full review of the current status of each topic. The articles are up-to-date and fully illustrated with in-text references that allow readers to easily access primary literature. While all entries are authoritative and valuable to those with advanced understanding of evolutionary biology, they are also intended to be accessible to both advanced undergraduate and graduate students. Broad topics include the history of evolutionary biology, population genetics, quantitative genetics; speciation, life history evolution, evolution of sex and mating systems, evolutionary biogeography, evolutionary developmental biology, molecular and genome evolution, coevolution, phylogenetic methods, microbial evolution, diversification of plants and fungi, diversification of animals, and applied evolution. Presents fully comprehensive content, allowing easy access to fundamental information and links to primary research Contains concise articles by leading experts in the field that ensures current coverage of each topic Provides ancillary learning tools like tables, illustrations, and multimedia features to assist with the comprehension process
