### 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.

• 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

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

• 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 5oC. Ohter tents produce temperatures of 10oC and 15oC.
• 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 41oF, 50oF, and 59oF 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.

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