Neurosymbolic AI: Foundations and Applications
Language: English
Published by Wiley-IEEE Press, 2026
- Hardcover
- New
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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In English.
Seller Inventory # ria9781394302376_new
- Title
- Neurosymbolic AI: Foundations and Applications
- Publisher
- Wiley-IEEE Press
- Publication year
- 2026
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1394302371
- ISBN 13
- 9781394302376
An up-to-date and expert discussion of neuro-symbolic artificial intelligence development
In Neuro-symbolic AI: Foundations and Applications, a team of distinguished researchers delivers a comprehensive overview of the emerging field of neuro-symbolic artificial intelligence. Expert contributors explain the integration of symbolic representations with neural networks, demonstrating state-of-the-art practices in the field.
The book fosters collaboration amongst diverse disciplines and promotes a deeper understanding of the challenges posed by deep learning, including generalizability, explainability, and robustness. It is an authoritative, self-contained reference text that provides a solid foundation for newcomers to the field as well as seasoned researchers and developers.
Readers will find:
- A systematic perspective on the foundations of neuro-development AI system development
- Comprehensive explorations of key concepts in neuro-symbolic artificial intelligence
- Discussions of real-world applications of neuro-symbolic AI in fields such as healthcare, finance, autonomous driving, and the military
- Complete treatments of the foundations of neuro-symbolic AI from multiple disciplinary perspectives, including computer science, software engineering, and academic research
Perfect for researchers and professionals in artificial intelligence involved industries, including autonomous driving, military, healthcare, and finance, Neuro-symbolic AI: Foundations and Applications will also benefit students of computer science, software engineering, data science, and machine learning.
"Synopsis" may belong to another edition of this title.
About the Author
Alvaro Velasquez, PhD, is a Program Manager at Defense Advanced Research Projects Agency. He is also a Visiting Professor in the Department of Computer Science at the University of Colorado Boulder.
Houbing Herbert Song, PhD, is a Tenured Associate Professor, Director of the NSF Center for Aviation Big Data Analytics (Planning), an Associate Director for Leadership of the DOT Transportation Cybersecurity Center for Advanced Research and Education, and Director of Security and Optimization for the Networked Globe Laboratory at the University of Maryland.
Pradeep Ravikumar, PhD, is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin.
S. Shankar Sastry, PhD, is a Professor of Electrical Engineering and Computer Sciences, Bio-Engineering, and Mechanical Engineering at the University of California, Berkeley.
Sandeep Neema, PhD, is a Professor in the Department of Computer Science and the Director of the Institute for Software Integrated Systems at Vanderbilt University.
"About the title" may belong to another edition of this title.
Ria Christie Collections
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