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Books in Artificial intelligence

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    • Observing the User Experience

      • 3rd Edition
      • January 1, 2026
      • Elizabeth Goodman + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 1 5 5 6 9 1
      • eBook
        9 7 8 0 1 2 8 1 8 9 2 7 6
      Observing the User Experience: A Practitioner's Guide to User Research, Third Edition helps readers bridge the gap to understand what users want and need from their product. Filled with real-world experience and a wealth of practical information, the book presents a complete toolbox of techniques to help designers, developers, and other stakeholders see through the eyes of their users. Sections discuss the benefits of end-user research and the ways it fits into the development of useful, desirable, and successful products and present techniques for understanding people’s needs, desires, and abilities, providing a basis for developing better products, whether Web, software, or mobile-based.Final chapters explain the communication and application of research results.

    • Transforming Industries, Empowering Societies

      • 1st Edition
      • January 12, 2026
      • Parikshit Narendra Mahalle + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 2 8 7 8 7
      • eBook
        9 7 8 0 4 4 3 3 2 8 7 9 4
      With the ever-increasing use of AI technologies, ethical considerations take on greater importance. Human-centric AI emphasizes transparency, making sure that AI systems work in a way that users can comprehend and trust. Additionally, it addresses bias and discrimination issues, ensuring fairness and inclusion in the design and implementation of AI apps. By emphasizing user experience, security, and human-centric AI, the goal is to improve collaboration between people and machines, rather than replacing human decisions, creating a future where technology is a force for good, benefiting both businesses and society. Written from a technological point of view, Industry 5.0 for Society 5.0 explores the impact of cutting-edge technologies, including the Internet of Things, cloud, artificial intelligence, and digital twin, on individuals and community, and considers how they can be used to solve societal problems. The book considers how these technologies can positively affect industry, healthcare, agriculture, design and manufacture, contributing to the development of a sustainable environment that ultimately creates a positive and mutually beneficial relationship between people and AI.

    • Federated Learning for the Metaverse

      • 1st Edition
      • January 11, 2026
      • Noor Zaman Jhanjhi + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 8 9 3 9
      • eBook
        9 7 8 0 4 4 3 3 3 8 9 4 6
      Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.

    • Wearable Sensing and Assistive Devices for Robotic Rehabilitation

      • 1st Edition
      • April 1, 2026
      • Wei Meng + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 0 4 6 3 4
      • eBook
        9 7 8 0 4 4 3 4 0 4 6 4 1
      “Wearable Sensing and Assistive Devices for Robotic Rehabilitation” provides an overview of current research and developments in the field of innovative technologies for advanced wearable sensing and assistive devices in medical rehabilitation. This book presents a systematic investigation of the wearable acquisition and deep learning-based processing of biological signals and the applications with wearable robotic devices. It provides fundamental bio-mechatronics engineering knowledge to analyze and design new wearable sensing and assistive devices. It includes human wearable sensors design and development, biological signals acquisition and processing, brain-computer interface and neuromuscular interfaces, wearable exoskeleton and soft robotic devices, as well as human-centered interactive robot control.

    • Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics

      • 1st Edition
      • February 1, 2026
      • Sayooj Aby Jose + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 2 3 4 0
      • eBook
        9 7 8 0 4 4 3 3 3 2 3 5 7
      Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics offers a comprehensive exploration of innovative methodologies at the intersection of mathematics, biology, and medicine. This book delves into advanced mathematical modeling, artificial intelligence, and computational intelligence, providing essential tools for understanding and managing complex disease dynamics. Covering a wide range of topics, including fractional-order modeling, optimal control strategies, and privacy-preserving technologies, it addresses critical challenges in public health and healthcare systems. With contributions from leading experts, this volume bridges theoretical advancements and practical applications, making it an invaluable resource for researchers, healthcare professionals, and academics seeking interdisciplinary solutions to global health issues.

    • Digital Supply Chain Transformation

      • 1st Edition
      • April 1, 2026
      • Vinaytosh Mishra
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 9 9 5 0
      • eBook
        9 7 8 0 4 4 3 3 3 9 9 6 7
      Digital Supply Chain Transformation: Implementing Technology, Analytics, and Data-Driven Solutions delves into the intricate world of supply chain management, emphasizing the role of digital transformation in modern supply chains. Through a blend of theoretical learning and practical applications, readers will gain a deep understanding of foundational supply chain principles while exploring emerging trends and technologies reshaping the industry. Topics such as system dynamics modelling, machine learning, artificial intelligence, and end-to-end visibility will be explored in-depth, equipping readers with the tools and knowledge needed to excel in the rapidly evolving landscape of supply chain management. There is a growing recognition that supply chain management can be significantly improved by leveraging modern technologies, such as machine learning and generative AI, to enhance efficiency and accuracy. Digital Supply Chain Transformation: Implementing Technology, Analytics, and Data-Driven Solutions helps readers:Comprehend core principles and elements of supply chain management and its pivotal role in businesses and industries.Recognize the significance of digital transformation in supply chains, understanding the tools, technologies, and strategies essential for a successful transformation.Evalu... the importance of end-to-end supply chain visibility and employ methods and technologies to enhance this visibility in practical scenarios.Apply system dynamics modelling techniques to address complex supply chain problems and optimize supply chain processes.Utilize supply chain analytics and tools to make data-driven decisions, enhancing efficiency and reducing operational costs.Understand the potential of machine learning and artificial intelligence in supply chains, applying these technologies to innovate and solve real-world supply chain challenges.Identify and analyze emerging trends in supply chain management, anticipating future challenges and opportunities in the field.Demonstrate the ability to apply theoretical knowledge to practical scenarios, devising solutions for real-world supply chain challenges.Criticall... evaluate supply chain strategies, technologies, and solutions, recommending improvements and innovations based on informed analysis.

    • Autonomous Vehicle Safety Solutions

      • 1st Edition
      • January 1, 2026
      • Aparna Kumari
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 5 2 8 0
      • eBook
        9 7 8 0 4 4 3 3 3 5 2 9 7
      Autonomous Vehicle Safety Solutions: Foundations, Technologies, and Prospects for the Future addresses the dynamically evolving state of the art that traverses and brings together automotive engineering, electronics engineering, and computer science. Its technical overview of smart vehicles' capabilities, propelled by headway in artificial intelligence and sensor technologies, enables in-depth understanding of the safety-assurance complexities that guide their design and operation.The comprehensive volume distinguishes itself for its treatment of several exciting, emerging opportunities and trends, including machine learning algorithms, V2X connectivity, and cybersecurity. Up-to-date applications are featured through practical examples and expert insights, bringing additional value to a discourse which underscores the critical need for ongoing safety advancements and adaptability in the fast-moving context of autonomous driving systems, with their related implications on sustainability and society as a whole.The outcome is a cornerstone resource for academia and industry alike that encourages further transformative, interdisciplinary investigations to bring safety solutions to maturity and subsequent rigorous testing for validation standards to be defined, thus realizing, in a future not distant from now, a scenario where self-driving vehicles can co-exist seamlessly with traditional modes of transportation and also integrate reliably, efficiently, and without risks within the larger infrastructure.

    • Learning-Driven Game Theory for AI

      • 1st Edition
      • February 1, 2026
      • Mehdi Salimi + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 3 8 5 2 3
      • eBook
        9 7 8 0 4 4 3 4 3 8 5 3 0
      Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.

    • Computational Intelligence in Surveillance Systems Using Image Processing

      • 1st Edition
      • March 1, 2026
      • Jay Kumar Pandey + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 4 0 8 2
      • eBook
        9 7 8 0 4 4 3 3 6 4 0 9 9
      Traditional surveillance systems struggle to process large volumes of visual data, identify specific objects or behaviors, and adapt to dynamic environments. Computational intelligence, which encompasses techniques like artificial intelligence (AI), machine learning (ML), and computer vision, offers powerful tools to address these challenges by enabling automated analysis, pattern recognition, and decision-making based on visual data. Computational Intelligence in Surveillance Systems Using Image Processing addresses the unique challenges and ethical considerations of applying AI and ML, offering a nuanced understanding of the regulatory landscape. It provides insights into the responsible development and deployment of technologies to unlock the transformative potential of computational intelligence to revolutionize surveillance systems and advance the capabilities of security and monitoring across various sectors.

    • Quantum Theory, Decision Making and Social Dynamics

      • 1st Edition
      • February 1, 2026
      • Tofigh Allahviranloo + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 4 9 0 7
      • eBook
        9 7 8 0 4 4 3 3 6 4 9 1 4
      Quantum Theory, Decision Making and Social Dynamics is an innovative exploration of the intersection of quantum theory, decision-making, and social networks. As quantum theory continues to permeate various fields, there is a growing need for accessible resources that elucidate its principles and applications. This book aims to fill that gap by illuminating the complex interplay between quantum theory and social dynamics, particularly in the context of decision-making. It addresses the challenges of understanding and applying quantum theory in social dynamics and equips readers with the knowledge to harness its potential in decision-making processes. The book is organized into nine chapters, each delving into a specific aspect of quantum theory and its applications. Chapter 1 provides an overview of quantum theory, tracing its historical development and key principles. Chapter 2 explores the integration of quantum theory with fuzzy systems, highlighting real-world applications and emerging trends. In Chapter 3, the focus shifts to the application of quantum theory in social networks, including quantum social network models and case studies. Chapter 4 examines decision-making processes within social networks, while Chapter 5 introduces and analyzes quantum decision-making models. Chapter 6 delves into quantum graph theory, discussing quantum graphs, walks, and algorithms. The subsequent chapters address the challenges and limitations of quantum decision-making (Chapter 7), future directions for the field (Chapter 8), and conclude with a summary of key points and final thoughts (Chapter 9). Quantum Theory, Decision Making and Social Dynamics is an invaluable resource for graduate students, researchers, and professionals in the fields of applied mathematics, computer science, physics, and social sciences interested in applying quantum approaches to the study of decision-making. These readers often face challenges in understanding complex quantum concepts, applying quantum theory to social networks, and utilizing quantum decision-making models. This book provides a solid foundation in quantum theory, introduces its applications in diverse areas, and prepares readers to navigate the quantum age with confidence. By offering a comprehensive overview and practical insights, this book empowers its audience to appreciate the profound impact of quantum theory on social network dynamics and decision-making.

Related subjects

Artificial intelligence expert systems and knowledge based systems

Artificial intelligence general

Cognitive science

Computer human interaction

Evolutionary computation genetic algorithms programming

Fuzzy logic

Machine learning

Natural language and computational linguistics

Neural networks

Planning and scheduling

Reasoning

Robotics and autonomous systems