An Interactive Jupyter Book Companion
Based on “Artificial Intelligence: A Textbook” by Charu C. Aggarwal
Instructor: Khalil Chebil
Welcome¶
Welcome to this interactive companion to the study of Artificial Intelligence! This Jupyter Book is designed to complement your learning journey through the Advanced Artificial Intelligence course, combining theoretical foundations with practical Python implementations.
Book Structure¶
This textbook strikes a balance between deductive reasoning and inductive learning approaches to artificial intelligence, organized into three major parts:
Part I: Deductive Reasoning (Chapters 1-5)¶
Methods based on logic, search, and systematic reasoning:
Chapter 1: Introduction to Artificial Intelligence
Chapter 2: Searching State Spaces
Chapter 3: Multiagent Search
Chapter 4: Propositional Logic
Chapter 5: First-Order Logic
Part II: Inductive Learning (Chapters 6-10)¶
Data-driven machine learning approaches:
Chapter 6: Machine Learning - The Inductive View
Chapter 7: Neural Networks
Chapter 8: Domain-Specific Neural Architectures
Chapter 9: Unsupervised Learning
Chapter 10: Reinforcement Learning
Part III: Integrating Reasoning and Learning (Chapters 11-13)¶
Advanced topics combining both paradigms:
Chapter 11: Probabilistic Graphical Models
Chapter 12: Knowledge Graphs
Chapter 13: Integrating Reasoning and Learning