Neuro-Symbolic Artificial Intelligence.

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Bibliographic Details
Online Access: Full text (Emerson users only)
Main Author: Hitzler, P.
Contributors: Sarker, M. K.
Format: eBook
Language:English
Published: : IOS Press, Incorporated, 2022.
Series:Frontiers in Artificial Intelligence and Applications Ser.
Subjects:
Local Note:ProQuest Ebook Central
Table of Contents:
  • Intro
  • Title Page
  • Preface: The 3rd AI wave is coming, and it needs a theory
  • Introduction
  • Contents
  • Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation
  • Chapter 2. Symbolic Reasoning in Latent Space: Classical Planning as an Example
  • Chapter 3. Logic Meets Learning: From Aristotle to Neural Networks
  • Chapter 4. Graph Reasoning Networks and Applications
  • Chapter 5. Answering Natural-Language Questions with Neuro-Symbolic Knowledge Bases
  • Chapter 6. Tractable Boolean and Arithmetic Circuits
  • Chapter 7. Neuro-Symbolic AI = Neural + Logical + Probabilistic AI
  • Chapter 8. A Constraint-Based Approach to Learning and Reasoning
  • Chapter 9. Spike-Based Symbolic Computations on Bit Strings and Numbers
  • Chapter 10. Explainable Neuro-Symbolic Hierarchical Reinforcement Learning
  • Chapter 11. Neuro-Symbolic Semantic Reasoning
  • Chapter 12. Learning Reasoning Strategies in End-to-End Differentiable Proving
  • Chapter 13. Generalizable Neuro-Symbolic Systems for Commonsense Question Answering
  • Chapter 14. Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning
  • Chapter 15. Human-Centered Concept Explanations for Neural Networks
  • Chapter 16. Abductive Learning
  • Chapter 17. Logic Tensor Networks: Theory and Applications
  • Author Index.