Download Free A Biologically Inspired Model Of Decision Making Controlled By Random Neural Activity Book in PDF and EPUB Free Download. You can read online A Biologically Inspired Model Of Decision Making Controlled By Random Neural Activity and write the review.

Goal-Directed Decision Making: Computations and Neural Circuits examines the role of goal-directed choice. It begins with an examination of the computations performed by associated circuits, but then moves on to in-depth examinations on how goal-directed learning interacts with other forms of choice and response selection. This is the only book that embraces the multidisciplinary nature of this area of decision-making, integrating our knowledge of goal-directed decision-making from basic, computational, clinical, and ethology research into a single resource that is invaluable for neuroscientists, psychologists and computer scientists alike. The book presents discussions on the broader field of decision-making and how it has expanded to incorporate ideas related to flexible behaviors, such as cognitive control, economic choice, and Bayesian inference, as well as the influences that motivation, context and cues have on behavior and decision-making. Details the neural circuits functionally involved in goal-directed decision-making and the computations these circuits perform Discusses changes in goal-directed decision-making spurred by development and disorders, and within real-world applications, including social contexts and addiction Synthesizes neuroscience, psychology and computer science research to offer a unique perspective on the central and emerging issues in goal-directed decision-making
In the years since it first published, Neuroeconomics: Decision Making and the Brain has become the standard reference and textbook in the burgeoning field of neuroeconomics. The second edition, a nearly complete revision of this landmark book, will set a new standard. This new edition features five sections designed to serve as both classroom-friendly introductions to each of the major subareas in neuroeconomics, and as advanced synopses of all that has been accomplished in the last two decades in this rapidly expanding academic discipline. The first of these sections provides useful introductions to the disciplines of microeconomics, the psychology of judgment and decision, computational neuroscience, and anthropology for scholars and students seeking interdisciplinary breadth. The second section provides an overview of how human and animal preferences are represented in the mammalian nervous systems. Chapters on risk, time preferences, social preferences, emotion, pharmacology, and common neural currencies—each written by leading experts—lay out the foundations of neuroeconomic thought. The third section contains both overview and in-depth chapters on the fundamentals of reinforcement learning, value learning, and value representation. The fourth section, “The Neural Mechanisms for Choice, integrates what is known about the decision-making architecture into state-of-the-art models of how we make choices. The final section embeds these mechanisms in a larger social context, showing how these mechanisms function during social decision-making in both humans and animals. The book provides a historically rich exposition in each of its chapters and emphasizes both the accomplishments and the controversies in the field. A clear explanatory style and a single expository voice characterize all chapters, making core issues in economics, psychology, and neuroscience accessible to scholars from all disciplines. The volume is essential reading for anyone interested in neuroeconomics in particular or decision making in general. Editors and contributing authors are among the acknowledged experts and founders in the field, making this the authoritative reference for neuroeconomics Suitable as an advanced undergraduate or graduate textbook as well as a thorough reference for active researchers Introductory chapters on economics, psychology, neuroscience, and anthropology provide students and scholars from any discipline with the keys to understanding this interdisciplinary field Detailed chapters on subjects that include reinforcement learning, risk, inter-temporal choice, drift-diffusion models, game theory, and prospect theory make this an invaluable reference Published in association with the Society for Neuroeconomics—www.neuroeconomics.org Full-color presentation throughout with numerous carefully selected illustrations to highlight key concepts
This book starts with an introduction to the basic concepts of multistability, then illustrates how multistability arises in different systems and explains the main mechanisms of multistability emergence. A special attention is given to noise which can convert a multistable deterministic system to a monostable stochastic one. Furthermore, the most important applications of multistability in different areas of science, engineering and technology are given attention throughout the book, including electronic circuits, lasers, secure communication, and human perception. The book aims to provide a first approach to multistability for readers, who are interested in understanding its fundamental concepts and applications in several fields. This book will be useful not only to researchers and engineers focusing on interdisciplinary studies, but also to graduate students and technicians. Both theoreticians and experimentalists will rely on it, in fields ranging from mathematics and laser physics to neuroscience and astronomy. The book is intended to fill a gap in the literature, to stimulate new discussions and bring some fundamental issues to a deeper level of understanding of the mechanisms underlying self-organization of matter and world complexity.
This book includes best-selected, high-quality research papers presented at Second International Conference on Biologically Inspired Techniques in Many Criteria Decision Making (BITMDM 2021) organized by Department of Information & Communication Technology, Fakir Mohan University, Balasore, Odisha, India, during December 20-21, 2021. This proceeding presents the recent advances in techniques which are biologically inspired and their usage in the field of many criteria decision making. The topics covered are biologically inspired algorithms, nature-inspired algorithms, multi-criteria optimization, multi-criteria decision making, data mining, big-data analysis, cloud computing, IOT, machine learning and soft computing, smart technologies, crypt-analysis, cognitive informatics, computational intelligence, artificial intelligence and machine learning, data management exploration and mining, computational intelligence, and signal and image processing.
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques. Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.
Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.