Chapter 19: Learning from Examples — Exercises

Chapter 19: Learning from Examples¶

Russell & Norvig, Artificial Intelligence: A Modern Approach (4th ed.), end-of-chapter Exercise prompts — full text is included on this site (same material as the exercises/ch19/ sources in the aima monorepo).

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Exercise 19.1¶

Show, by translating into conjunctive normal form and applying resolution, that the conclusion drawn on page dbsig-page concerning Brazilians is sound.

Exercise 19.2¶

For each of the following determinations, write down the logical representation and explain why the determination is true (if it is):

1. Design and denomination determine the mass of a coin.
   

2. For a given program, input determines output.
   

3. Climate, food intake, exercise, and metabolism determine weight gain and loss.
   

4. Baldness is determined by the baldness (or lack thereof) of one’s maternal grandfather.
   

Exercise 19.3¶

For each of the following determinations, write down the logical representation and explain why the determination is true (if it is):

1. Zip code determines the state (U.S.).
   

2. Design and denomination determine the mass of a coin.
   

3. Climate, food intake, exercise, and metabolism determine weight gain and loss.
   

4. Baldness is determined by the baldness (or lack thereof) of one’s maternal grandfather.
   

Exercise 19.4¶

Would a probabilistic version of determinations be useful? Suggest a definition.

Exercise 19.5¶

Fill in the missing values for the clauses $C_1$ or $C_2$ (or both) in the following sets of clauses, given that $C$ is the resolvent of $C_1$ and $C_2$:

1. $C = {True} \Rightarrow P(A,B)$, $C_1 = P(x,y) \Rightarrow Q(x,y)$, $C_2 = ??$.
   

2. $C = {True} \Rightarrow P(A,B)$, $C_1 = ??$, $C_2 = ??$.
   

3. $C = P(x,y) \Rightarrow P(x,f(y))$, $C_1 = ??$, $C_2 = ??$.
   

If there is more than one possible solution, provide one example of each different kind.

Exercise 19.6¶

Suppose one writes a logic program that carries out a resolution inference step. That is, let ${Resolve}(c_1,c_2,c)$ succeed if $c$ is the result of resolving $c_1$ and $c_2$. Normally, ${Resolve}$ would be used as part of a theorem prover by calling it with $c_1$ and $c_2$ instantiated to particular clauses, thereby generating the resolvent $c$. Now suppose instead that we call it with $c$ instantiated and $c_1$ and $c_2$ uninstantiated. Will this succeed in generating the appropriate results of an inverse resolution step? Would you need any special modifications to the logic programming system for this to work?

Exercise 19.7¶

Suppose that is considering adding a literal to a clause using a binary predicate $P$ and that previous literals (including the head of the clause) contain five different variables.

1. How many functionally different literals can be generated? Two literals are functionally identical if they differ only in the names of the new variables that they contain.
   

2. Can you find a general formula for the number of different literals with a predicate of arity $r$ when there are $n$ variables previously used?
   

3. Why does not allow literals that contain no previously used variables?
   

Exercise 19.8¶

Using the data from the family tree in Figure family2-figure, or a subset thereof, apply the algorithm to learn a definition for the ${Ancestor}$ predicate.