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The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.
This volume summarizes the new developments that made subcellular proteomics a rapidly expanding area. It examines the different levels of subcellular organization and their specific methodologies. In addition, the book includes coverage of systems biology that deals with the integration of the data derived from these different levels to produce a synthetic description of the cell as a system.
Despite the intensive experimental and theoretical studies for over a century, the general processes involved in neural control of pasture and movement, in learning of motor behaviour in healthy subjects and in adaptation in pathology were and remain a challenging problems for the scientists in the field of sensorimotor control. The book is the outcome of the Advanced Research Workshop Sensorimotor Control, where the focus was on the state and the perspectives of the study in the field.
"A work of enormous breadth, likely to pleasantly surprise both general readers and experts."—New York Times Book Review This revolutionary book provides fresh answers to long-standing questions of human origins and consciousness. Drawing on his breakthrough research in comparative neuroscience, Terrence Deacon offers a wealth of insights into the significance of symbolic thinking: from the co-evolutionary exchange between language and brains over two million years of hominid evolution to the ethical repercussions that followed man's newfound access to other people's thoughts and emotions. Informing these insights is a new understanding of how Darwinian processes underlie the brain's development and function as well as its evolution. In contrast to much contemporary neuroscience that treats the brain as no more or less than a computer, Deacon provides a new clarity of vision into the mechanism of mind. It injects a renewed sense of adventure into the experience of being human.
From translating the patient’s medical records and test results to providing recommendations, the neuropsychological evaluation incorporates the science and practice of neuropsychology, neurology, and psychological sciences. The Little Black Book of Neuropsychology brings the practice and study of neuropsychology into concise step-by-step focus—without skimping on scientific quality. This one-of-a-kind assessment reference complements standard textbooks by outlining signs, symptoms, and complaints according to neuropsychological domain (such as memory, language, or executive function), with descriptions of possible deficits involved, inpatient and outpatient assessment methods, and possible etiologies. Additional chapters offer a more traditional approach to evaluation, discussing specific neurological disorders and diseases in terms of their clinical features, neuroanatomical correlates, and assessment and treatment considerations. Chapters in psychometrics provide for initial understanding of brain-behavior interpretation as well as more advanced principals for neuropsychology practice including new diagnostic concepts and analysis of change in performance over time. For the trainee, beginning clinician or seasoned expert, this user-friendly presentation incorporating ‘quick reference guides’ throughout which will add to the practice armentarium of beginning and seasoned clinicians alike. Key features of The Black Book of Neuropsychology: Concise framework for understanding the neuropsychological referral. Symptoms/syndromes presented in a handy outline format, with dozens of charts and tables. Review of basic neurobehavioral examination procedure. Attention to professional issues, including advances in psychometrics and diagnoses, including tables for reliable change for many commonly used tests. Special “Writing Reports like You Mean It” section and guidelines for answering referral questions. Includes appendices of practical information, including neuropsychological formulary. The Little Black Book of Neuropsychology is an indispensable resource for the range of practitioners and scientists interested in brain-behavior relationships. Particular emphasis is provided for trainees in neuropsychology and neuropsychologists. However, the easy to use format and concise presentation is likely to be of particular value to interns, residents, and fellows studying neurology, neurological surgery, psychiatry, and nurses. Finally, teachers of neuropsychological and neurological assessment may also find this book useful as a classroom text. "There is no other book in the field that covers the scope of material that is inside this comprehensive text. The work might be best summed up as being a clinical neuropsychology postdoctoral residency in a book, with the most up to date information available, so that it is also an indispensible book for practicing neuropsychologists in addition to students and residents...There is really no book like this available today. It skillfully brings together the most important foundationsof clinical neuropsychology with the 'nuts and bolts' of every facet of assessment. It also reminds the more weathered neuropsychologists among us of the essential value of neuropsychological assessment...the impact of the disease on the patient’s cognitive functioning and behavior may only be objectively quantified through a neuropsychological assessment." Arch Clin Neuropsychol (2011) first published online June 13, 2011 Read the full review acn.oxfordjournals.org
This book has brought together leading investigators who work in the new arena of brain connectomics. This includes ‘macro-connectome’ efforts to comprehensively chart long-distance pathways and functional networks; ‘micro-connectome’ efforts to identify every neuron, axon, dendrite, synapse, and glial process within restricted brain regions; and ‘meso-connectome’ efforts to systematically map both local and long-distance connections using anatomical tracers. This book highlights cutting-edge methods that can accelerate progress in elucidating static ‘hard-wired’ circuits of the brain as well as dynamic interactions that are vital for brain function. The power of connectomic approaches in characterizing abnormal circuits in the many brain disorders that afflict humankind is considered. Experts in computational neuroscience and network theory provide perspectives needed for synthesizing across different scales in space and time. Altogether, this book provides an integrated view of the challenges and opportunities in deciphering brain circuits in health and disease.
Modern neuroscience research is inherently multidisciplinary, with a wide variety of cutting edge new techniques to explore multiple levels of investigation. This Third Edition of Guide to Research Techniques in Neuroscience provides a comprehensive overview of classical and cutting edge methods including their utility, limitations, and how data are presented in the literature. This book can be used as an introduction to neuroscience techniques for anyone new to the field or as a reference for any neuroscientist while reading papers or attending talks. - Nearly 200 updated full-color illustrations to clearly convey the theory and practice of neuroscience methods - Expands on techniques from previous editions and covers many new techniques including in vivo calcium imaging, fiber photometry, RNA-Seq, brain spheroids, CRISPR-Cas9 genome editing, and more - Clear, straightforward explanations of each technique for anyone new to the field - A broad scope of methods, from noninvasive brain imaging in human subjects, to electrophysiology in animal models, to recombinant DNA technology in test tubes, to transfection of neurons in cell culture - Detailed recommendations on where to find protocols and other resources for specific techniques - "Walk-through" boxes that guide readers through experiments step-by-step
This book sets out the necessary processes and challenges involved in modeling student thinking, understanding and learning. The chapters look at the centrality of models for knowledge claims in science education and explore the modeling of mental processes, knowledge, cognitive development and conceptual learning. The conclusion outlines significant implications for science teachers and those researching in this field. This highly useful work provides models of scientific thinking from different field and analyses the processes by which we can arrive at claims about the minds of others. The author highlights the logical impossibility of ever knowing for sure what someone else knows, understands or thinks, and makes the case that researchers in science education need to be much more explicit about the extent to which research onto learners’ ideas in science is necessarily a process of developing models. Through this book we learn that research reports should acknowledge the role of modeling and avoid making claims that are much less tentative than is justified as this can lead to misleading and sometimes contrary findings in the literature. In everyday life we commonly take it for granted that finding out what another knows or thinks is a relatively trivial or straightforward process. We come to take the ‘mental register’ (the way we talk about the ‘contents’ of minds) for granted and so teachers and researchers may readily underestimate the challenges involved in their work.