Requirements Midterm Exam
                    Graduate AI (Fall 2004)
                     Tu., October 26, 10a
                           Draft 

The exam is open-books you can bring everything including calculators, and 
your favorite pet, but friends and other human beings are not permitted! 


Relevant material of the Russel textbook:
Chapter 3 (with the exception of 3.6)
Chapter 4 (excluding MA*, SMA* and excluding section 4.5)
Chapeter 6 (Sections 6.1, 6.2, and 6.3)
All transparencies that were presented in class that discussed search

Evolutionary Computing 
textbook pages 116-119
Eiben/Smith Article excluding sections 2.4.2 and 2.6 (you
                                  can expect pretty basic questions)
Transparencies discussed in Class

Logical Reasoning
Section 7.5 (only read those sections that center on resolution)
Sections 8.1, 8.2, and 8.3
Sections 9.1, 9.2, and 9.5 (only resolution is relevant)
Transparencies that were discussed in class
Translation natural language to FOPL 
Making proofs using the resolution method

Decision Trees (all questions refer to decision trees and not to general aspects 
                of learning).
Section 18.3
Transparencies discussed in class


Material that was discussed in class that is relevant
for the midterm exam (but not necessarily is discussed in the textbook):

a) Backtracking algorithm
b) Simulated Annealling and Hill Climbing Algorithms
c) some logical reasoning transparencies
d) evolutionary computing transparencies 

In general, the midterm exam will focus on the following topics: 
formulating search problems, finding heuristics for search problems, "general" 
search algorithm, breadth first search, uniform cost search, depth-first seach, 
backtracking, best-first search, A*, RBFS, hill climbing, randomized hill climbing, 
simulated annealing; decision trees; alpha-beta; basic knowledge of evolutionary computing
techniques; natural language to FOPL, making resolution proof, problems with respect
to making resolution proofs for FOPL.