Download Group C

CS/sem-7/CS-702/2009
2009
ARTIFICIAL INTELLIGENCE
Time Allotted: 3 hours
Full Marks: 70
Group-A
(Multiple Choice Questions)
1. Choose the correct alternatives for the following:
10 x 1 =10
i) ~Q and PQ results resolvent ~P. This special case of resolution is known as
a)
b)
c)
d)
Chaining
Modus Ponens
Modus Tollens
None of these
ii) Which of the following is a component of a typical expert system
a) Inference engine
b) Knowledge base & learning module
c) Working memory
d) All of the above
iii) A search algorithm is complete if it
a) always finds the optimal solution
b) always finds a solution if there is one
c) finds all possible solutions
d) never finds a solution
iv) Which of the following techniques uses randomness for avoiding getting
trapped in local maxima?
a) Best first search
b) Local beam search
c) Simulated annealing
d) Gradient descent
v)
vi)
Declarative knowledge is
a) passive knowledge expressed as statement of facts about the world
b) compiled knowledge related to the performance of some task
c) some belief or hypothesis
d) all of the above
Skolem function is used in
Page 1 of 4
a)
b)
c)
d)
vii)
unification algorithm
natural deduction
conversion to clausal form
none of these
A formula is in conjunctive normal form if it is a
a) sum of elementary product
b) product of elementary sum
c) product of literals
d) both a & b
viii) A greedy search uses a heuristic function to
a) expand the node that appears to be closest to the goal
b) expand the node that is closest to the goal
c) expand the node that is the most expensive
d ) expand the leftmost node
ix) What is the difference between the cost function and heuristic function
portions of the A* evaluation function?
a) A cost function returns the actual cost from current node to goal, while the
heuristic function returns the estimated cost from current node to goal
b) A cost function returns the estimated cost from start node to current node,
while the heuristic function returns the estimated cost from current node to goal
c) A cost function returns the estimated cost from current node to goal, while the
heuristic function returns the actual cost from start node to current node
d) A cost function returns the actual cost from start node to current node, while
the heuristic function returns the estimated cost from current node to goal.
x) An utility function is used in game playing to
a) estimate the expected utility of the game from a given position
b) compute the winner of the game based on number of pieces left
c) compute the utility of a terminal leaf in a game tree
d) compute the best move for the successor function
Group-B
(Short Answer Questions)
Answer any three
3 x 5 = 15
2. Differentiate among Data, Information, Belief, Hypothesis and Knowledge.
3. What is intelligent agent? Describe Utility Based agent.
4. Write Prolog/LISP clauses to find the maximum of a list of numbers.
5. Define soundness & completeness of a set of inference rules. Prove that resolution is
sound but not complete
6. Explain briefly AND –OR graph.
Page 2 of 4
Group C
[ Long Answer questions ]
Answer any three questions
7.
3 x 15 = 45
3+(4+4)+4
a) What is Constraint Satisfaction problem? Give example.
b) Given a full 5-gallon jug and an empty 2-gallon jug, the goal is to fill the 2-gallon
jug with exactly one gallon of water. You may use the following state space
formulation.
State = (x, y), where x is the number of gallons of water in the 5-gallon jug and y
is # of gallons in the 2-gallon jug
Initial State = (5,0)
Goal State = (*,1), where * means any amount
i) Write the production system for the above problem
ii) Create the search tree for the solution.
c) Briefly explain Hill climbing control strategy.
8.
4+5+6
st
a) Consider the following game tree in which static scores are all from the 1 player’s
point of view.
i) Suppose the 1st player is maximizing player. What move should be chosen?
ii) What nodes would not need to be examined using the alpha–beta pruning
procedure.
(7) (6)
(8)
(0) (2)
(3)
(0)
(-2) (6)
(2)
(5)
(8)
(9)
(2)
b) Solve the following 8-puzzle problem using A* algorithm
2 8 3
1 2 3
1 6 4
8 - 4
7 - 5
7 6 5
Initial state
Goal state
9.
(2x2)+5+6
Page 3 of 4
a) Represent the following sentences by predicate calculus wffs. (any two)
i)
Not all students take both AI & DBMS.
ii)
Some patients like all doctors.
iii)
Every student who takes Computer Architecture also takes Digital
Logic.
iv)
There is a woman who likes all men who do not smoke.
b) Convert the following expression into clausal form.
(x)(y){ (z) P(f(x),y,z)  [ (u) Q(x,u)  (v) R(y,v)] }
c) Give the predicate logic expression of the following sentence and then represent
them in semantic net.
i) Every man has beaten the thief
ii) All persons in the party loved every child
10.
4+4+4+3
a) What do you mean by Forward Reasoning & Backward reasoning? What factors
determine the choice of direction for a particular problem?
b) Discuss the scope & limitations of knowledge representation using proposition
logic and first order predicate logic.
a) Explain Dempster-Shafter Theory of statistical reasoning.
c) Define Horn Clause. Is P Q a horn clause? Justify your answer.
11.
5+2+3+3+2
a) Compare BFS with iterative deepening in terms of time and space complexity.
b) When a heuristic function is said to be consistent?
c) Show that if heuristics are consistent then the heuristics are admissible, but the
reverse is not true.
d) The f-values of the sequence of nodes expanded by algorithm A* is nondecreasing if heuristic function is consistent.
e) Discuss about informedness of a heuristic algorithm.
12.
5+(2x5)
a) “All people who are wealthy and smart are happy. Those people who can read are
smart. John can read and is wealthy. Happy people have exciting lives.”
Use resolution to answer the question “Can anyone be found with an
exciting lives”?
b) Write short notes on (any two)
i)
Genetic Algorithm
ii)
Fuzzy Logic
iii)
Knowledge Representation
_________________________________________________
Page 4 of 4