EAN: 9781098110758

Produktdaten aktualisiert am: 05.11.2024
Hersteller: - Hersteller-ArtNr. (MPN): - ASIN: -

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today primed with machine learning perception and deep reinforcement learning capabilities can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples minimal theory and a proven architectural framework author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students process operators data scientists machine learning algorithm experts and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated autonomous and human decision-making Unique advantages of autonomous AI for real-time decision-making with use cases How to design an autonomous AI from modular components and document your designs

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