CS534 ARTIFICIAL INTELLIGENCE. SPRING 98
PRACTICE PROBLEMS FOR FINAL EXAM

PROF. CAROLINA RUIZ
Department of Computer Science
Worcester Polytechnic Institute

• Reasoning under Uncertainty
  1. Russell and Norvig: 14.1, 14.3, 14.4,14.5,14.8,14.9,15.1,15.2,15.3.
  2. Additional Problems

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• Machine Learning - Decision Trees
  1. Russell and Norvig: 18.3, 18.6, 18.11

  2. Dean, Allen, and Aloimonos: Construct a minimal decision tree for the following set of training examples that helps a robot janitor predicting whether or not an office contains a recycling bin.

     	STATUS	FLOOR	DEPT.	OFFICE SIZE	RECYCLING BIN?
     1.	faculty	three	ee	large	no
     2.	staff	three	ee	small	no
     3.	faculty	four	cs	medium	yes
     4.	student	four	ee	large	yes
     5.	staff	five	cs	medium	no
     6.	faculty	five	cs	large	yes
     7.	student	three	ee	small	yes
     8.	staff	four	cs	medium	no

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• Machine Learning - Neural Nets
  1. Russell and Norvig: 19.3, 19.4, 19.6

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• Machine Learning - Genetic Algorithms
  1. Winston
     1. Suppose that you are testing various tent designs and tent materials for comfort in winter. The temperature outside the tent is -40 degrees. The temperature inside a tent of one design-material conmbination, warmed by your body heat and a small stove is 5^oC. Ohter tents produce temperatures of 10^oC and 15^oC.
        • Compute the chances of survival of each combination using the standard fitness method with inside temperature as the measure of quality (the warmer the better).
        • Now suppose that you have lost your Celsius thermometer, reducing you to measuring temperature with a Fahrenheit thermometer. Recalculate the chances of survival of each combination with the 41^oF, 50^oF, and 59^oF temperatures.
        • Comment why your results argue against the use of the standard method.
     2. Suppose that you are using the rank method to select candidates. Recall that the probability of picking the first-ranked candidate is p. If the first candidate is not pricked, then the probability of picking the second-ranked candidate is p (that is the second candidate's chance of survival is p*(1-p)), and so on, until only one candidate is left, in which case it is selected.
        • Suppose that you have five candidates. You decide to select one using the rank-space method with p=0.25. Compute the probabilities for each of the five as a function of rank.
        • What is peculiar about the probabilities that you computed in the previous part?
        • Can you avoid the pecularity you observed in part 2 by restricting the probability to a particular range?
  2. Dean, Allen, and Aloimonos: Discuss how you would represent and solve the traveling salesperson problem using genetic algorithms.

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• Machine Vision
  1. Russell and Norvig: 24.2, 24.3, 24.4, 24.5, 24.7