Computer Science 5541
Artificial Intelligence
Homework Assignment 5 (20 points)
Due December 15, 2009

1. For the following set of examples:
   • a1, b1, c1, d1, +
   • a2, b2, c2, d2, -
   • a3, b1, c3, d1, -
   • a2, b1, c2, d2, +
   • a1, b2, c3, d1, -
   • a2, b1, c2, d2, +
   • a3, b2, c3, d2, -
   • a2, b1, c3, d2, -
   Calculate the decision tree that would be produced by ID3, show all of your work.
2. A test for a rare disease is 99% accurate in identifying the disease when the person has the disease and 97% accurate when the person does not have the disease. .5% of the population has the disease. Rich takes the test and it comes up positive (the test indicates he may have the disease). Using Bayes rules, what is the likelihood Rich actually has the disease (hint: the probability that Rich has the disease plus the probability that Rich does not have the disease must add up to 1)? If he takes a second test, and the tests are conditionally independent, how likely is it that he has the disease?
3. How are reinforcement learning and partial order planning similar? How do they differ?