Study guide for the Artificial Intelligence Comprehensive Examination

This serves as a guide for students preparing for the Graduate Comprehensive Exam in Artificial Intelligence. The topics below cover the fundamental concepts of artificial intelligence. They include areas in search, representation, reasoning, planning, learning, and uncertainty.

Students need to be aware that some materials might not be covered by a particular instructor in the corresponding course (due to time and other factors) and they are expected, as graduate students, to be able to read and understand materials they might not have seen in class.

Books:

• Primary book for the covered materials:
  • Russell, S. & Norvig, P. (2010). Artificial Intelligence: A Modern Approach. Third Edition, Pearson. [AIMA3]
  -OR-
  • Russell, S. & Norvig, P. (2003). Artificial Intelligence: A Modern Approach. Second Edition, Prentice Hall. [AIMA2]

Topics:

• Problem Solving
  • Search: Breadth-first, Depth-first, Iterative Deepening Depth-first, Uniform-cost, Greedy Best-first, Hill climbing, and A* [AIMA3 Ch 3-4.2] or [AIMA2 Ch 3-4.3]
  • Constraint Satisfaction [AIMA3 Ch 6.1-6.4] or [AIMA2 Ch 5.1-5.2]
  • Game Playing: Minimax Trees and Alpha-Beta Pruning [AIMA3 Ch 5.1-5.3] or [AIMA2 Ch 6.1-6.3]
• Knowledge and Reasoning
  • Propositional logic [AIMA3 Ch 7.1-7.5] or [AIMA2 Ch 7.1-7.5]
  • Predicate (first-order) logic [AIMA3 8.1-8.3] or [AIMA2 Ch 8.1-8.3]
  • Inference [AIMA3 9.1-9.5.3] or [AIMA2 Ch 9.1 - page 300]
• Planning [AIMA3 Ch 10.1-10.2, 10.4.2, 10.4.4] or [AIMA2 Ch 11.1-11.3]
• Uncertainty [AIMA3 Ch 13] or [AIMA2 Ch 13]
• Learning: decision trees [AIMA3 Ch 18.1-18.3.4] or [AIMA2 Ch 18.1-18.3]

Updated August 29th, 2013 (from the previous version in ~2005)

• Added third edition of the primary book and references to it
• Removed alternative books
• Different chapter for Uncertainty