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.