Course Syllabus for CS 343:
Artificial Intelligence

Chapter numbers refer to the text: Artificial Intelligence: A Modern Approach (3rd ed) by Stuart Russell and Peter Norvig
  1. Introduction
    Chapters 1-2. Definition and history of AI
  2. Problem Solving
    Chapters 3, 4 (section 4.1), 5. Uninformed search, informed (heuristic) search, game playing.
  3. Knowledge and Reasoning
    Chapters 7-9, 12 (sections 12.5 and 12.6). Representing knowledge, propositional logic, first-order predicate logic, automated deduction: forward chaining, backward chaining, and resolution, frames, inheritance, and non-monotonic inference.
  4. Planning
    Chapter 10 (except section 10.3) Representing actions, situation calculus, classical planning algorithms.
  5. Uncertain Reasoning
    Chapters 13, 14 (except sections 14.5 and 14.7). Probability theory, Naive Bayes, Bayesian networks: representation and inference.
  6. Learning
    Chapter 18 (sections 18.1-18.4, 18.7) . Inductive learning for classification, decision-tree induction, neural-networks: representation and training.
  7. Natural Language Processing
    Chapter 23 (sections 23.1-23.3). Syntactic, semantic, and pragmatics analysis. Resolving ambiguity.
  8. Philosophy and Conclusions
    Chapters 26, 27. Arguments against the possiblity of AI.