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CS 540-1: Introduction to Artificial Intelligence
Final Exam: 2:45-4:45pm, December 16, 1994
Room B239, Van Vleck
CLOSED BOOK
(one page of notes allowed)
Write your answers on these pages and show your work. If you feel that a question is not fully specified, state any assumptions that you need to make in order to solve the problem. You may use the backs of these sheets for scratch work.
Write your name on this and all other pages of this exam. Make sure your exam contains seven problems on ten pages.
Name ________________________________________________
Student ID ________________________________________________
Problem Score Max Score
1 _____ 10
2 _____ 35
3 _____ 15
4 _____ 20
5 _____ 15
6 _____ 40
7 _____ 15
Total _____ 150
PROBLEM 1 - Planning (10 points)
Consider the following STRIPS operators:
Operator 1 Operator 3 preconditions: A ∧ C preconditions: B add list: B ∧ D add list: D delete list: C delete list: C Operator 2 Operator 4 preconditions: A ∧ D preconditions: A ∧ C add list: E add list: B delete list: A delete list: E
Assume the task is to construct a plan that correctly converts the initial state A ∧ B ∧ C into the final state D ∧ E
Show the initial state and its immediate descendants (i.e., neighbors) in the search space when:
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you are using standard state-based search to solve the problem
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you are using the STRIPS algorithm (goal-directed planning)
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you are using the TWEAK algorithm (non-linear planning) [you do not have to answer this precisely; simply illustrate the gist of TWEAK]
Part C. Now consider using the delta rule to train a perceptron on this data; this time you should consider training the threshold. Assume that the weight and the threshold are both initially -0.1, and let d =0.1. Draw the perceptron at the times requested below.
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before training
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after training on the first example above (explain the changes, if any)
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after training on the second example above (explain the changes, if any)
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Part D. Which search-control strategy does backpropagation use (e.g., depth-first search, beam search, best-first search, etc.)? What about ID3? Explain your answers.
PROBLEM 3 - Decision Trees (15 points)
Consider learning a decision tree that you could use to judge whether or not you will like a given restaurant. Assume you have chosen to use the following three features to describe restaurants, with the possible values shown.
Price ∈ {Low, Med, High} Type ∈ {Hamburgers, Pizza, Fish, Vegetarian}
Assume Quinlan’s ID3 algorithm is given the following set of classified training examples. Calculate the decision tree that ID3 would produce. Show all your work. (You may use the abbreviations that are used to describe the examples.)
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P = L T = H + P = L T = V + P = M T = F - P = M T = V + P = H T = P - hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh
lg is the base 2 log
lg(a*b) = lg(a) + lg(b) lg(a/b) = lg(a) - lg(b)
lg(1) = 0 lg(2) = 1 lg(3) = 1. lg(4) = 2 lg(5) = 2.
PROBLEM 5 - Resolution Theorem Proving (15 points)
Consider the following statements.
Every man has his eyes checked by the doctor.
No man checks his own eyes.
Everyone is either a man or a woman.
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Part A. Represent the English sentences above in FOPC.
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Part B. Represent the above FOPC in clausal form.
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Part C. Using resolution, show that the doctor is a woman.
PROBLEM 6 - Miscellaneous Questions (40 points)
Answer the following true (T) or false (F). Provide brief justifications of your answers.
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Breadth-first search is guaranteed to find the optimal solution.
Ans: _____ Just:
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Hill climbing and beam search, when the beam width is set to one, will always produce the same answer.
Ans: _____ Just:
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The horizon effect does not impact hill-climbing algorithms.
Ans: _____ Just:
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The qualification problem is an important issue in planning.
Ans: _____ Just:
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Using negation by failure is one way to address the frame problem.
Ans: _____ Just:
PROBLEM 7 - Common Lisp (15 points)
Assume you have started a fresh Lisp. What would the following Lisp expressions return? (If you think a Lisp error would result, write ERROR.) hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh
(append ’(1 2 3) (cons 1 nil))
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(* 4 (+ 5 3) (* (+ 2 4) 2))
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(list (append ’(1 2) (rest (cons (first ’(3)) ’((4)))) ))
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(defun mystery (x y) "A mystery function." (cond ((null x) y) (t (append (mystery (rest x) y) (list (first x)))))) MYSTERY (mystery ’(1 2) ’(a b))
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(setf x ’(1 2 3)) (1 2 3) (setf (second x) ’new) NEW x
The end - have a good vacation!
