Course Syllabus for CS 343:
Artificial Intelligence



Chapter numbers refer to the text: Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
  1. Introduction
    Chapters 1-2. Definition and history of AI
  2. Problem Solving
    Chapters 3, 4, 6. Uninformed search, informed (heuristic) search, game playing.
  3. Knowledge and Reasoning
    Chapters 7-9, 10 (sections 10.6 and 10.7). Representing knowledge, propositional logic, first-order predicate logic, automated deduction: forward chaining, backward chaining, and resolution, frames, inheritance, and non-monotonic inference.
  4. Planning
    Chapters 10 (section 10.3), 11 (sections 11.1 - 11.3). Representing actions, situation calculus, total-order and partial-order planning algorithms.
  5. Uncertain Reasoning
    Chapters 13, 14 (sections 14.1-14.4, 14.6). Probability theory, Naive Bayes, Bayesian networks: representation and inference.
  6. Learning
    Chapters 18, 20 (section 20.5). Inductive learning for classification, decision-tree induction, neural-networks: representation and training.
  7. Natural Language Processing
    Chapter 22. Syntactic, semantic, and pragmatics analysis. Resolving ambiguity.
  8. Philosophy and Conclusions
    Chapters 26-27. Arguments against the possiblity of AI.