Students will be familiar with standard blind and heuristic search 
techniques used in artificial intelligence applications and with 
their computational complexity.  Students will be familiar with 
standard methods of knowledge representation used in
artificial intelligence. Students will be familiar with the most 
common philosophical issues raised by artificial intelligence 
research and with the most common philosophical positions taken 
on these issues. Students will also be expected to be
familiar with several of the standard methods associated with 
topics listed below, but students will not be expected to achieve 
familiarity with all of these methods in any single offering of the course.

Several of the following topics will be included in any 
offering of the course.

What is artificial intelligence?
Exhaustive search methods
Heuristic search methods
Computational complexity of search methods
Representing knowledge using logic
Representing knowledge using frames
Representing knowledge using semantic nets
Uncertainty and Bayes' Theorem
Uncertainty and certainty factors
Uncertainty and nonmonotonic reasoning
Partially ordered planning
Hierarchical planning
Learning by rule induction
Learning using neural nets
Parsing and natural language processing
Pattern recognition
Computer vision
Robotics
Can machines think?