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Software Engineering Sample Test I

By Edward Stewart,2014-04-19 06:30
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Artificial Intelligence Sample Test. Disclaimer: The following sample test is provided to give you an idea of the type of problems that might be on our test

    Artificial Intelligence Sample Test

Disclaimer: The following sample test is provided to give you an idea of the type of

    problems that might be on our test. These questions are not meant to represent a

    comprehensive review of all relevant material. As always, anything covered in “fair

    game.” Please be especially sure to go over the quizzes that we have had in class. You are almost certainly going to see something similar on the test.

The test will be closed book and closed notes. You will not be permitted to use any

    source other than your own thought processes (non-artificial intelligence).

1.) How would you define intelligence? Defend your definition.

    2.) How would you define Artificial Intelligence? Defend your definition.

3.) Describe the Turing Test.

    4.) What do you think is the significance of the Turing Test? Why?

    5.) Suppose that the enrollment department at a college wants to predict the number of

    accepted applicants that will actually enroll as Freshmen in the fall. They have a lot

    of historical data describing student attributes and whether or not they came to the

    college. How might you develop a system that predicts whether a particular student

    will enroll using:

    a.) Rule-induction

    b.) Genetic algorithms

    6.) Describe the minimax algorithm. What result does it produce?

    7.) Given the same game state and the same maximum depth, can the alpha-beta

    algorithm produce an answer different than a minimax algorithm? If so, describe

    the conditions.

8.) Describe 3 different methods of tree search.

9.) Describe alpha-beta in non-technical terms.

    10.) In the A* algorithm, what is meant by admissibility? Give an example of an

    admissible heuristic for an application that we haven’t talked about in class.

    11.) Given two genes from a tree-based genetic program, show how crossover and

    mutation might work. Describe the process.

    12.) Describe the initialization process for genetic programming.

13.) Given two genes:

    F F F F F F F F

    M M M M M M M M

    Use 2 crossover points to produce their offspring.

14.) What role does mutation play in a genetic algorithm?

15.) What does entropy measure?

16.) What are some problems with rule-induction?

17.) What can we say about nodes on the open and closed lists in an A* algorithm

    when the heuristic is monotonic and admissible? How does the algorithm

    determine which node to expand next?

18.) What is a static evaluation function? Why do we need it?

    19.) Can “aspirated” alpha-beta search cause a search to take longer? Explain.

20.) Write a prolog clause that removes all occurrences of an item from a list.

     For example,

     removeItem(a, [a, b, [a, b], [c, d]], X).

     X = [b, [b],[c, d]].

21.) What can we conclude from the Fundamental Theorem of Genetic Algorithms?

22. Consider the statement, “If it is raining in Hanoi, then the streets are wet in

    Lynchburg.” How might you write this using propositional logic? How might you

    write it using predicate calculus?

23. How would you write each of the following using predicate calculus?

    a. There is at least one person who likes predicate calculus.

    b. Everyone likes artificial intelligence.

24. What is “Abduction?” Why is it useful?

25. Perform resolution on the following normal form clauses:

    { (~A,B), (~A, ~B,C), A, ~C) }

What can you conclude from this result?

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