Critical study companion · AIMA 3e · 2010 → 2026
The classical AI backbone.
A structured companion to Russell and Norvig’s third edition, organised into concepts, questions, flashcards and checks, with the limits of its 2010 perspective kept visible.
This is not a comprehensive bank of modern AI and it does not replace the current fourth edition. It is an annotated archive of the rational-agent, search, logic, planning, uncertainty and learning ideas that still organise technical reasoning in 2026.
How the companion works
Retrieval, critique, connection.
The source is transformed into learning objects: concepts, questions, answers, examples, misconceptions, flashcards and quiz items. Modern commentary distinguishes durable foundations from outdated architecture.
Source and reading path
One source, clearly bounded.
The processed source is Artificial Intelligence: A Modern Approach, third edition, by Russell and Norvig. The remaining titles are a suggested reading path, not processed sections of this companion.
Book 001 master map
Seven phases. Twenty-seven chapters. One backbone.
Russell & Norvig’s 27 chapters group into seven thematic phases. Each phase carries its theme, the AI domains it covers, the essential questions it answers, and a jump-link into the question bank below.
Master domains
Twenty-three domains, one taxonomy.
Each domain is a slice of the AI field with a question count and difficulty range. Tap a card to filter the question bank.
Master question bank
Browse, flashcard, quiz, or run an interview.
Filter by difficulty, domain, phase or type. Toggle mind-bending, interview, founder or research lenses. Click any card to expand the full answer.
Book 001 synthesis
Core thesis, strongest ideas, limitations, modern relevance.
A condensed view of what the book teaches, where it fits in modern AI, the durable ideas, the honest limits of the 3rd edition, and the open questions it raises for 2026 readers.
Reading path
The foundation is not the frontier.
Deep learning, probabilistic ML, reinforcement learning, AI engineering, alignment and economics extend the classical foundation. These are recommended next sources; they are not represented as completed work here.
Source & methodology
A learning system, not a substitute for the books.
Why this exists
This knowledge bank is built from source books and papers, but it does not replace them. The goal is to extract the durable ideas, organise them into questions, and create a learning system that helps readers understand, test, and connect concepts across the AI field.
Current baseline: AIMA fourth edition. The authors’ fourth-edition preface documents expanded treatment of machine learning, deep learning, probabilistic programming and multiagent systems.
The point of the companion.
A field as broad as AI cannot be carried as a list. The useful skill is retrieving a concept, stating its assumptions, connecting it to a modern system and recognising when the source has become historically informative rather than current.