CSC 411: Artificial Intelligence

(Fall 2006)

Assignment 3: Chapters 5, 6, 7

Due by November 9, Thursday, 2006

1. Chapter 5: Bayes’ theorem. Suppose an automobile insurance company classifies a driver as good, average, or bad. Of all their insured drivers, 25% are classified good, 50% are average, and 25% are bad. Suppose for the coming year, a good driver has a 5% chance of having an accident, and average driver has 15% chance of having an accident, and a bad driver has a 25% chance. If you had an accident in the past year, what is the probability that you are a good driver?

2. Chapter 6: Production Systems. In our class, we introduced Example 6.2.2 of the textbook, where the knight’s tour problem is presented and production rules for the 3´3 knight problem are proposed. Example 6.2.3 (pp.209-210) generalizes the knight’s tour solution to the full 8´8 chessboard and designed some production rules. Using the rule in Example 6.2.3 as a model, write the eight move rules needed for the full 8´8 version of the knight’s tour.

3. Chapter 6: In Section 2.4 (pp.73-76), Example 3.3.5 (pp. 115-116), and Example 4.2.1 (pp.143-144), the financial advisor problem is discussed. Using predicate calculates as a representation language:

i) Write the problem explicitly as a production system

ii) Generate the state space and stages of working memory for the data-driven solution to Example 3.3.5

iii) Repeat b for a goal-driven solution

4. Chapter 7: Translate each of the following sentences into predicate calculus, conceptual dependencies, and conceptual graphs:

“Jane gave Tom an ice cream cone.”

“Basketball players are tall.”

“Paul cut down the tree with an axe.”

“Place all the ingredients in a bowl and mix thoroughly.”

5. Chapter 7: The operations join and restrict (Section 7.2.4) defines a generalization ordering on conceptual graphs, while specialization of conceptual graphs using join and restrict is not a truth-preserving operation.

i) Show that the generalization relation is transitive.

ii) Give an example that demonstrates that that restriction of a true graph is not necessarily true.

iii) Prove this, however, that the generalization of a true graph is always true.