Principles and Applications of Adaptive Artificial Intelligence
Principles and Applications of Adaptive Artificial Intelligence

Author: Lv, Zhihan

Publisher: IGI Global

Published: 2024-01-24

Total Pages: 332

ISBN-13:

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The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.

Principles of Adaptive Filters and Self-learning Systems
Principles of Adaptive Filters and Self-learning Systems

Author: Anthony Zaknich

Publisher: Springer Science & Business Media

Published: 2005-08-19

Total Pages: 397

ISBN-13: 1846281210

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Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems

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

Learning for Adaptive and Reactive Robot Control
Learning for Adaptive and Reactive Robot Control

Author: Aude Billard

Publisher: MIT Press

Published: 2022-02-08

Total Pages: 425

ISBN-13: 0262367017

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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.

Principles and Applications of Adaptive Artificial Intelligence
Principles and Applications of Adaptive Artificial Intelligence

Author: Zhihan Lv

Publisher:

Published: 2024

Total Pages: 0

ISBN-13:

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The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence , edited by Zhihan Lv of Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation issues in AI systems. It explores the latest concepts, technologies, and applications of adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, the handbook presents real-world cases, along with thorough analysis and relatable examples, making it an invaluable resource for practitioners seeking practical ideas and solutions in the field. Additionally, the book serves as a teaching material and reference guide for students and educators in AI-related disciplines, ensuring a deep understanding and exploration of the emerging discipline of Adaptive AI. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems. In a rapidly changing landscape, Principles and Applications of Adaptive Artificial Intelligence becomes the ultimate guide for researchers, professionals, and students, enabling them to unleash the full potential of Adaptive AI and revolutionize their research and applications.

Risk Assessment and Countermeasures for Cybersecurity
Risk Assessment and Countermeasures for Cybersecurity

Author: Almaiah, Mohammed Amin

Publisher: IGI Global

Published: 2024-05-01

Total Pages: 304

ISBN-13:

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The relentless growth of cyber threats poses an escalating challenge to our global community. The current landscape of cyber threats demands a proactive approach to cybersecurity, as the consequences of lapses in digital defense reverberate across industries and societies. From data breaches to sophisticated malware attacks, the vulnerabilities in our interconnected systems are glaring. As we stand at the precipice of a digital revolution, the need for a comprehensive understanding of cybersecurity risks and effective countermeasures has never been more pressing. Risk Assessment and Countermeasures for Cybersecurity is a book that clarifies many of these challenges in the realm of cybersecurity. It systematically navigates the web of security challenges, addressing issues that range from cybersecurity risk assessment to the deployment of the latest security countermeasures. As it confronts the threats lurking in the digital shadows, this book stands as a catalyst for change, encouraging academic scholars, researchers, and cybersecurity professionals to collectively fortify the foundations of our digital world.

Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems
Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems

Author: Uddin, M. Irfan

Publisher: IGI Global

Published: 2024-02-26

Total Pages: 307

ISBN-13:

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The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.

Empowering Low-Resource Languages With NLP Solutions
Empowering Low-Resource Languages With NLP Solutions

Author: Pakray, Partha

Publisher: IGI Global

Published: 2024-02-27

Total Pages: 328

ISBN-13:

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In our increasingly interconnected world, low-resource languages face the threat of oblivion. These linguistic gems, often spoken by marginalized communities, are at risk of fading away due to limited data and resources. The neglect of these languages not only erodes cultural diversity but also hinders effective communication, education, and social inclusion. Academics, practitioners, and policymakers grapple with the urgent need for a comprehensive solution to preserve and empower these vulnerable languages. Empowering Low-Resource Languages With NLP Solutions is a pioneering book that stands as the definitive answer to the pressing problem at hand. It tackles head-on the challenges that low-resource languages face in the realm of Natural Language Processing (NLP). Through real-world case studies, expert insights, and a comprehensive array of topics, this book equips its readers—academics, researchers, practitioners, and policymakers—with the tools, strategies, and ethical considerations needed to address the crisis facing low-resource languages.

Intelligent Systems and Control: Principles and Applications
Intelligent Systems and Control: Principles and Applications

Author: Laxmidhar Behera

Publisher: OUP India

Published: 2009-12-24

Total Pages: 388

ISBN-13: 9780198063155

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Intelligent Systems and Control: Principles and Applications is a textbook for undergraduate level courses on intelligent control, intelligent systems, adaptive control, and non-linear control. The book covers primers in neural networks, fuzzy logic, and non-linear control so that readers can easily follow intelligent control techniques.

AI and education
AI and education

Author: Miao, Fengchun

Publisher: UNESCO Publishing

Published: 2021-04-08

Total Pages: 50

ISBN-13: 9231004476

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Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]