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Neuro-symbolic artificial intelligencebridging logic and learning /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neuro-symbolic artificial intelligenceby Bikram Pratim Bhuyan ... [et al.].
Reminder of title:	bridging logic and learning /
other author:	Bhuyan, Bikram Pratim.
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xiii, 358 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence.
Online resource:	https://doi.org/10.1007/978-981-97-8171-3
ISBN:	9789819781713$q(electronic bk.)

Neuro-symbolic artificial intelligencebridging logic and learning /
Neuro-symbolic artificial intelligencebridging logic and learning /[electronic resource] :by Bikram Pratim Bhuyan ... [et al.]. - Singapore :Springer Nature Singapore :2025. - xiii, 358 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 11761860-9503 ;. - Studies in computational intelligence ;v. 216..

The Emergence of Neuro-Symbolic Artificial Intelligence -- Neuro-Symbolic AI: The Fusion of Symbolic Reasoning and Machine Learning -- Neuro-Symbolic AI: The Integration of Continuous Learning and Discrete Reasoning -- Knowledge Representation in Artificial Intelligence -- Rule-based Systems and Expert Systems -- Knowledge Graphs: Representation and Reasoning -- Feedforward Neural Networks and Backpropagation -- Convolution in Neural Networks -- Recurrent Neural Networks (RNNs): Capturing the Dynamics of Sequences -- Overview of Neuro-Symbolic Integration Frameworks -- Learning from Symbolic Knowledge for Neural Networks -- Neural Extraction of Symbolic Knowledge -- Graph Neural Networks in Neural-Symbolic Computing -- Rule-based Reasoning in Neural Networks -- Common Sense Reasoning for Neuro-Symbolic AI -- Explainable and Trustworthy AI with Neuro-Symbolic Approaches -- Neuro-Symbolic AI in various Domains -- Towards Artificial General Intelligence? -- Learning and Reasoning over Higher Ordered Geometrical Structures -- Key Takeaways from Neuro-Symbolic AI.

This book highlights and attempts to fill a crucial gap in the existing literature by providing a comprehensive exploration of the emerging field of neuro-symbolic AI. It introduces the concept of neuro-symbolic AI, highlighting its fusion of symbolic reasoning and machine learning. The book covers symbolic AI and knowledge representation, neural networks and deep learning, neuro-symbolic integration approaches, reasoning and inference techniques, applications in healthcare and robotics, as well as challenges and future directions. By combining the power of symbolic logic and knowledge representation with the flexibility of neural networks, neuro-symbolic AI offers the potential for more interpretable and trustworthy AI systems. This book is a valuable resource for researchers, practitioners, and students interested in understanding and applying neuro-symbolic AI.

ISBN: 9789819781713$q(electronic bk.)

Standard No.: 10.1007/978-981-97-8171-3doiSubjects--Topical Terms:

194058
Artificial intelligence.

LC Class. No.: Q335

Dewey Class. No.: 006.3

Neuro-symbolic artificial intelligencebridging logic and learning /
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505 0 $a The Emergence of Neuro-Symbolic Artificial Intelligence -- Neuro-Symbolic AI: The Fusion of Symbolic Reasoning and Machine Learning -- Neuro-Symbolic AI: The Integration of Continuous Learning and Discrete Reasoning -- Knowledge Representation in Artificial Intelligence -- Rule-based Systems and Expert Systems -- Knowledge Graphs: Representation and Reasoning -- Feedforward Neural Networks and Backpropagation -- Convolution in Neural Networks -- Recurrent Neural Networks (RNNs): Capturing the Dynamics of Sequences -- Overview of Neuro-Symbolic Integration Frameworks -- Learning from Symbolic Knowledge for Neural Networks -- Neural Extraction of Symbolic Knowledge -- Graph Neural Networks in Neural-Symbolic Computing -- Rule-based Reasoning in Neural Networks -- Common Sense Reasoning for Neuro-Symbolic AI -- Explainable and Trustworthy AI with Neuro-Symbolic Approaches -- Neuro-Symbolic AI in various Domains -- Towards Artificial General Intelligence? -- Learning and Reasoning over Higher Ordered Geometrical Structures -- Key Takeaways from Neuro-Symbolic AI.
520 $a This book highlights and attempts to fill a crucial gap in the existing literature by providing a comprehensive exploration of the emerging field of neuro-symbolic AI. It introduces the concept of neuro-symbolic AI, highlighting its fusion of symbolic reasoning and machine learning. The book covers symbolic AI and knowledge representation, neural networks and deep learning, neuro-symbolic integration approaches, reasoning and inference techniques, applications in healthcare and robotics, as well as challenges and future directions. By combining the power of symbolic logic and knowledge representation with the flexibility of neural networks, neuro-symbolic AI offers the potential for more interpretable and trustworthy AI systems. This book is a valuable resource for researchers, practitioners, and students interested in understanding and applying neuro-symbolic AI.
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