STUPIDSID
1 (a)
How problem characteristics help in the selection of AI technique? Explain these characteristics with possible examples.
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1 (b)
Explain the method of Hill climbing. Also explain the problems associated
with hill climbing and possible solutions.
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2 (a)
Consider the following initial and goal configuration for 8-puzzle problem.
Draw the search tree for initial three iterations of A* algorithm to reach
from initial state to goal state. Assume suitable heuristic function for the
same.
| Initial state | ||
| 1 | 2 | |
| 3 | 4 | 5 |
| 6 | 7 | 8 |
| Goal State | ||
| 1 | 2 | 3 |
| 8 | 4 | |
| 7 | 6 | 5 |
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2 (b)
Write a Prolog program for finding a set, which is result of the intersection of the two given sets.
Hint: Goal: intersect([1, 2, 3], [2, 3, 4], A)
A = [2, 3]
Goal: intersect([d, f, g], [a, b, c ], X)
X = [ ]
Hint: Goal: intersect([1, 2, 3], [2, 3, 4], A)
A = [2, 3]
Goal: intersect([d, f, g], [a, b, c ], X)
X = [ ]
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2 (c)
Write a Prolog program to merge two sequentially ordered (ascending) 07
lists into one ordered list.
Hint: Goal: merge([1, 3, 5, 7], [0, 2, 4, 6], L)
L = [0, 1, 2, 3, 4, 5, 6, 7]
Goal: merge([a, c], [b, d], [a, b, c, d])
Yes
Hint: Goal: merge([1, 3, 5, 7], [0, 2, 4, 6], L)
L = [0, 1, 2, 3, 4, 5, 6, 7]
Goal: merge([a, c], [b, d], [a, b, c, d])
Yes
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3 (a)
Explain different approaches of knowledge representation.
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3 (b)
Consider the following axioms:
1. Anyone whom Mary loves is a football star.
2. Any student who does not pass does not play.
3. John is a student.
4. Any student who does not study does not pass.
5. Anyone who does not play is not a football star.
Prove using resolution process that 'If John does not study, then Mary does not love John'.
1. Anyone whom Mary loves is a football star.
2. Any student who does not pass does not play.
3. John is a student.
4. Any student who does not study does not pass.
5. Anyone who does not play is not a football star.
Prove using resolution process that 'If John does not study, then Mary does not love John'.
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3 (c)
Explain the steps of unification in predicate logic. Also discuss the steps of
converting predicate logic wffs to clause form.
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3 (d)
Explain following terms with reference to Prolog programming language:
Clauses, Predicates, Domains, Goal, Cut, Fail, Inference engine
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4 (a)
Explain forward and backward reasoning in detail with suitable examples of
Each.
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4 (b)
What is nonmonotonic reasoning? Explain different subtypes of
nonmonotonic reasoning in brief.
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4 (c)
Define 'certainty factor'. How does certainty factor help in dealing with
uncertainty? Explain with reference to rule based system.
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4 (d)
Explain followings:
(i) Semantic net.
(ii) Frames.
(i) Semantic net.
(ii) Frames.
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5 (a)
Explain goal stack planning in detail.
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5 (b)
Enlist the phases of natural language understanding. Describe the role of
each phase in brief.
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5 (c)
Explain perceptron learning algorithm for training a neural network. What
are the limitations of this algorithm?
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5 (d)
Explain followings with reference to expert system:
(i) Expert system shell.
(ii) Knowledge acquisition.
(i) Expert system shell.
(ii) Knowledge acquisition.
7 M
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