Adaptive Artificial Intelligence: Fundamentals, Challenges and Applications (eng)

Master the next frontier of technology with this book, which provides an in-depth guide to adaptive artificial intelligence and its ability to create flexible, self-governed systems in dynamic industries.

Adaptive artificial intelligence represents a significant advancement in the development of AI systems, particularly within various industries that require robust, flexible, and responsive technologies. Unlike traditional AI, which operates based on pre-defined models and static data, adaptive AI is designed to learn and evolve in real time, making it particularly valuable in dynamic and unpredictable environments. This capability is increasingly important in disciplines such as autonomous systems, healthcare, finance, and industrial automation, where the ability to adapt to new information and changing conditions is crucial.

In industry development, adaptive AI drives innovation by enabling systems that can continuously improve their performance and decision-making processes without the need for constant human intervention. This leads to more efficient operations, reduced downtime, and enhanced outcomes across sectors. As industries increasingly rely on AI for critical functions, the adaptive capability of these systems becomes a cornerstone for achieving higher levels of automation, reliability, and intelligence in technological solutions.

Readers will find the book:

• Introduces the emerging concept of adaptive artificial intelligence;
• Explores the many applications of adaptive artificial intelligence across various industries;
• Provides comprehensive coverage of reinforcement learning for different domains.

Audience

Research scholars, IT professionals, engineering students, network administrators, artificial intelligence and deep learning experts, and government research agencies looking to innovate with the power of artificial intelligence.

P. Pavan Kumar, PhD is an associate professor in the Department of Artificial Intelligence and Data Science at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India. He has published more than 20 scholarly peer-reviewed research articles in international journals and two Indian patents. His research interests include real-time systems, multi-core systems, high-performance systems, and computer vision.

Grandhi Suresh Kumar, PhD is an associate professor and Associate Dean of Academics in the School of Science and Technology at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India with more than ten years of experience. He has published one authored book, one edited book, one book chapter, and more than 15 articles. His research interests include intelligent manufacturing, robotics, sustainable energy solutions, CO2 capture, and applications of AI in mechanical engineering.

Ajay Kumar Jena, PhD is an assistant professor and Associate Dean in the School of Computer Engineering at the Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. He has published three books, seven book chapters, and 61 research papers in various international journals and conferences. His research interests include blockchain, object-oriented software testing, software engineering, data science, soft computing, and machine learning.

Sandeep Kumar Panda, PhD is a professor and an Associate Dean in the School of Science and Technology at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India. He has published six books, several book chapters, and 80 articles in international journals and conferences. His research interests include blockchain technology, W3, metaverse, the Internet of Things, AI, and cloud computing.

S. Balamurugan, PhD is the Director of Research, iRCS, an Indian technological research and consulting firm. He has published more than 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of research experience using various cutting-edge technologies, he provides expert guidance in technology forecasting and decision-making for leading companies and startups.