Knowledge-Infused Learning
Neurosymbolic AI for Explainability, Interpretability, and Safety
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Product details:
- Publisher Cambridge University Press
- Date of Publication 31 January 2026
- ISBN 9781009513746
- Binding Hardback
- No. of pages310 pages
- Language English 700
Categories
Short description:
Introduces an emerging field that blends statistical models with symbolic knowledge to make AI safer and more explainable.
MoreLong description:
Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.
'Professor Amit Sheth is a leading expert in knowledge-fused learning. The topics covered by this book are important to advance state-of-the-art AI. As our understanding of generative AI deepens, we ask what the next frontiers of AI are. This timely book offers a refreshing answer that explores AI research beyond large language models.' Huan Liu, Arizona State University
Table of Contents:
1. Introduction; 2. Knowledge graphs for explainability and interpretability; 3. Knowledge-infused learning: the subsumer to neurosymbolic AI; 4. Shallow infusion of knowledge; 5. Semi-deep infusion learning; 6. Deep knowledge-infused learning; 7. Process knowledge-infused learning; 8. Knowledge-infused conversational NLP; 9. Neurosymbolic large language models; References; Index.
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