Engineering Neurosymbolic Artificial Intelligence: The Integration of Knowledge and Learning (Cognitive Computation & Engineering Series)

Thomas, Gareth Morgan

ISBN 13: 9798309062362

Edité par Independently published, 2025

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N° de réf. du vendeur I-9798309062362

Détails bibliographiques

• Titre: Engineering Neurosymbolic Artificial Intelligence: The Integration of Knowledge and Learning (Cognitive Computation & Engineering Series)
• Éditeur: Independently published
• Date de parution: 2025
• Langue: anglais
• ISBN à 13 chiffres: 9798309062362
• Reliure: Couverture souple
• État de l'article: New

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Synopsis

Unlock the Future of AI

The next revolution in artificial intelligence is here. Engineering Neurosymbolic Artificial Intelligence explores the powerful fusion of deep learning and symbolic reasoning, paving the way for AI systems that can learn, reason, and generalize beyond pattern recognition.

This comprehensive guide takes you beyond conventional deep learning, introducing neurosymbolic AI—a cutting-edge approach that integrates machine learning with structured reasoning to create AI that is more explainable, adaptable, and efficient.

What’s Inside

• The Evolution of AI: From rule-based systems to statistical learning and hybrid intelligence
• Mathematical Foundations: Logic, probabilistic reasoning, statistical learning theory, and optimization
• Knowledge Representation: Ontologies, knowledge graphs, and neural-symbolic models
• AI for Physics and Scientific Discovery: Physics-informed neural networks, differentiable physics engines, and hybrid reasoning systems
• Advanced Learning Mechanisms: Supervised, self-supervised, and zero-shot learning combined with symbolic methods
• Cutting-Edge Reasoning Systems: Theorem proving, probabilistic logic, and neural-symbolic inference
• Neural-Symbolic Integration: Combining deep learning with logical structures for superior AI performance
• Real-World Applications: Robotics, natural language understanding, visual intelligence, and more

A Rigorous Mathematical Approach

Unlike general AI books, this work includes a dedicated mathematical section covering logic, set theory, probability, statistics, and optimization—ensuring a solid foundation for mastering neurosymbolic AI.

Who Should Read This Book?

• AI Researchers & Engineers seeking to develop next-generation intelligent systems
• Data Scientists & Machine Learning Practitioners looking to enhance AI reasoning capabilities
• Students & Academics interested in a deeper understanding of AI beyond deep learning
• Industry Professionals in robotics, healthcare, finance, and automation who need advanced AI solutions

Why This Book?

Deep learning alone has limits. Engineering Neurosymbolic Artificial Intelligence equips you with the knowledge to build AI systems that think, reason, and adapt—ushering in a new era of intelligent technology.

Order now and take your AI expertise to the next level.