Adaptive Artificial Intelligence: Fundamentals, Challenges and Applications

ISBN 10: 1394389043 / ISBN 13: 9781394389049

Editore: Wiley-Scrivener, 2025

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Dati bibliografici

• Titolo: Adaptive Artificial Intelligence: Fundamentals, Challenges and Applications
• Editore: Wiley-Scrivener
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 1394389043
• ISBN 13: 9781394389049
• Rilegatura: Rilegato
• Condizione: New

Descrizione articolo

Riassunto

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.