Quantum-like Networks: An Approach To Neural Behavior Through Their Mathematics And Logic
Quantum-like Networks: An Approach To Neural Behavior Through Their Mathematics And Logic

Author: Stephen A Selesnick

Publisher: World Scientific

Published: 2022-08-03

Total Pages: 354

ISBN-13: 9811260710

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Do brains compute? If they do, what do they compute and how do they do it? The first part of the book introduces the development of a model that simulates actual biological neurons more closely than do current standard models of neural networks, as well as the deduction of its physics-like and computational properties from first principles. The second part presents a collection of applications of the model to memory formation and loss, a general syntax for memory retrieval, language itself, and certain forms of aphasia. A linear development of the discussion with proofs in situ is employed by the author, making the book essentially self-contained. A pair of helpful appendices are provided to acquaint the reader with necessary fundamentals of topics in logic and mathematics. Quantum-like Networks: An Approach to Neural Behavior through their Mathematics and Logic will show you an entirely new approach to an ancient subject.

Quantum Models of Cognition and Decision
Quantum Models of Cognition and Decision

Author: Jerome R. Busemeyer

Publisher: Cambridge University Press

Published: 2012-07-26

Total Pages: 425

ISBN-13: 110701199X

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Introduces principles drawn from quantum theory to present a new framework for modeling human cognition and decision.

World Congress on Neural Networks
World Congress on Neural Networks

Author: Paul Werbos

Publisher: Routledge

Published: 2021-09-10

Total Pages: 916

ISBN-13: 1317713419

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Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.

Supervised Learning with Quantum Computers
Supervised Learning with Quantum Computers

Author: Maria Schuld

Publisher: Springer

Published: 2018-08-30

Total Pages: 293

ISBN-13: 3319964240

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Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.

Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing
Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing

Author: Om Prakash Jena

Publisher: CRC Press

Published: 2022-06-22

Total Pages: 206

ISBN-13: 1000600270

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This book looks at industry change patterns and innovations (such as artificial intelligence, machine learning, big data analysis, and blockchain support and efficiency technology) that are speeding up industrial transformation, industrial infrastructure, biodiversity, and productivity. This book focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing. It also offers insights into manufacturing, logistics, and supply chain, where systems have undergone an industrial transformation. It discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure. It goes on to cover the effects that the Fourth Industrial Revolution has on industrial infrastructures and looks at the current industry change patterns and innovations that are accelerating industrial transformation activities. Researchers, scholars, and students from different countries will appreciate this book for its real-world applications and knowledge acquisition. This book targets manufacturers, industry owners, product developers, scientists, logistics, and supply chain engineers. Focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing Offers insights into manufacturing, logistics, and supply chain where systems have undergone an industrial transformation Discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure Covers the effects that the 4th Industrial Revolution has on industrial infrastructures Looks at industry change patterns and innovations that are speeding up industrial transformation activities

Interactive Granular Computations in Networks and Systems Engineering: A Practical Perspective
Interactive Granular Computations in Networks and Systems Engineering: A Practical Perspective

Author: Andrzej Jankowski

Publisher: Springer

Published: 2017-06-25

Total Pages: 663

ISBN-13: 3319576275

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The book outlines selected projects conducted under the supervision of the author. Moreover, it discusses significant relations between Interactive Granular Computing (IGrC) and numerous dynamically developing scientific domains worldwide, along with features characteristic of the author’s approach to IGrC. The results presented are a continuation and elaboration of various aspects of Wisdom Technology, initiated and developed in cooperation with Professor Andrzej Skowron. Based on the empirical findings from these projects, the author explores the following areas: (a) understanding the causes of the theory and practice gap problem (TPGP) in complex systems engineering (CSE); (b) generalizing computing models of complex adaptive systems (CAS) (in particular, natural computing models) by constructing an interactive granular computing (IGrC) model of networks of interrelated interacting complex granules (c-granules), belonging to a single agent and/or to a group of agents; (c) developing methodologies based on the IGrC model to minimize the negative consequences of the TPGP. The book introduces approaches to the above issues, using the proposed IGrC model. In particular, the IGrC model refers to the key mechanisms used to control the processes related to the implementation of CSE projects. One of the main aims was to develop a mechanism of IGrC control over computations that model a project’s implementation processes to maximize the chances of its success, while at the same time minimizing the emerging risks. In this regard, the IGrC control is usually performed by means of properly selected and enforced (among project participants) project principles. These principles constitute examples of c-granules, expressed by complex vague concepts (represented by c-granules too). The c-granules evolve with time (in particular, the meaning of the concepts is also subject of change). This methodology is illustrated using project principles applied by the author during the implementation of the POLTAX, AlgoTradix, Merix, and Excavio projects outlined in the book.

Natural and Artificial Intelligence
Natural and Artificial Intelligence

Author: A. de Callataÿ

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 695

ISBN-13: 1483297810

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How does the mind work? How is data stored in the brain? How does the mental world connect with the physical world? The hybrid system developed in this book shows a radically new view on the brain. Briefly, in this model memory remains permanent by changing the homeostasis rebuilding the neuronal organelles. These transformations are approximately abstracted as all-or-none operations. Thus the computer-like neural systems become plausible biological models. This illustrated book shows how artificial animals with such brains learn invariant methods of behavior control from their repeated actions. These robots can make decisions in any circumstances and reason by analogy whenever possible.This new and expanded edition includes a prologue exploring the problems which have stopped the development of fully fledged brain models. The causes of these deadlocks are listed as potential misconceptions about brain principles, neural networks, nervous systems, robotics, programming and decision logic.

Artificial Intelligence in the Age of Neural Networks and Brain Computing
Artificial Intelligence in the Age of Neural Networks and Brain Computing

Author: Robert Kozma

Publisher: Academic Press

Published: 2023-10-11

Total Pages: 398

ISBN-13: 0323958168

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Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks