COMPSCI 570 – Artificial Intelligence Qualifying Exam
Wednesday, August 22, 2012
9:00 A - 12:00 Noon
D106

Exam is Closed Book

COMPSCI 570: Qualifying Exam Syllabus

Topics Covered for Algorithms and Representations for Artificial Intelligence:

• Search
  • Uninformed search
  • Informed search
  • Constraint Satisfaction
• Game Playing
  • Minimax
  • alpha-beta search
  • Introduction to game theory
• Logic and Knowledge Representation
  • Propositional logic
  • First order logic
  • Theorem Proving
• Reasoning under uncertainty
  • Probability
  • Bayes nets
  • Hidden Markov models and tracking
• Planning
  • Classical planning
  • Decision theory
  • Stochastic planning (MDPs)

Prerequisites for COMPSCI 570 (provided for reference):

• Programming skills: You should be able to write and debug programs in C, C++, or Java without drama and without handholding
• Ability to do short proofs
• Facility with core computer science concepts:
  • Computational complexity
  • Analysis of algorithms
• Facility with mathematics concepts:
  • Some calculus
  • Basic Probability and statistics helpful but not required

Reference:

• Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig

Sample Exam:

• Fall 2011
• Fall 2010
• Fall 2008