2008 Rajiv Gandhi Proudyogiki Vishwavidyalaya(Technical University) Computer M.C.A M.C.A.(Fourth Semester) EXAMINATION, Dec., 2008 Question paper
MCA-401
M.C.A.(Fourth Semester) EXAMINATION, Dec., 2008
ARTIFICIAL INTELLIGENCE AND APPLICATIONS
(MCA-401)
Time : Three Hours
Maximum Marks : 100
Minimum Pass Marks : 40
Note : Attempt any one question from each Unit.All questions carry equal marks. Answers should
be brief and to the point.
Unit - I
1.(a) Why AI can be defined as the solution of exponentially hard problems in P-time (or less) ?
Other definitions of AI that are 'human' oriented
(b) The following Prolog relation appends a list A to list B to
give a list C.
append ([],Y,Y).
append([H|T],Y,[H|Z]) :- append (T,Y,Z).
Using the append relation, write a Prolog predicate insert(X,Y,Z) that is true if X can be
inserted into a list Y to give a list Z. Your relation should be capable of using backtracking
to generate all lists obtained from Y by inserting X at some point,using a query such as :
insert(c,[a,b],Z).
to obtain Z =[c,a,b],Z=[a,c,b], and Z=[a,b,c] it should generated each possibility
exactly onec.
Using the insert relation,write Prolog predicate perm (X,Y) that is true if a list Y is a
permutation of a list X. Your predicate should respond to a query such as perm ([a,b,c],Y) by
using backtracking to generate all permutations of the given list.
Or
2.(a) "AI is becoming less conspicuous yet more essential". Comment.
(b) How to write a "Hello World" programme in Lisp ?
Unit - II
3.(a) Describe the role of heuristics and the need for tradeoffs between optimality and efficiency.
(b) Explain how simulated annealing can be used to reduce search complexity and contrast its
operation with classic search techniques ?
Or
4.(a) Characterize the components of non-monotonic reasoning and its usefulness as a
representational mechanisms for belief systems.
(b) Give an example of a problem for which breadth first search would work better than depth first
search.
Unit - III
5. Consider the following story of the play Macbeth, by William Shakespeare. The characters are
Macbeth, Lady-Macbeth. Duncan and Macduff. Macbeth is an evil noble. lady Macbeth is a greedy
ambitious woman. Duncan is a king. Macduff is a loyal noble. Macbeth is weak because Macbeth
married Lady Macbeth and because Lady Macbeth is greedy. Lady Macbeth persuades Macbeth
to want to be king. Macbeth murders Duncan using a knife because Macbeth wants to be king and
because Macbeth is evil. Lady Macbeth kills Lady-Macbeth. Macduff is angry because Macbeth
murdered Duncan and because Macduff is loyal to Duncan. Macduff kills Macbeth. Construct a
semantic network representing the above story. Show the chain of reasoning leading to Macduff
killing Macbeth. It is possible to change the story so that Lady Macbeth is unable to Persuade
Macbeth to want to be king. Augment the storyto provide a reason for Lady Macbeth's inability
to persuade. Macbeth to want to be king. Update the semantic network to reflect the new
situation.
Or
6.(a) Illustrate the use of predicate logic to represent the knowledge with suitable example.
(b) Devise a semantic network capable of representing propositions of the following kinds :
John loves Mary more than she loves him.
John thinks that Mary does not love him.
John thinks that Mary does not love him, but she does love him.
Unit - IV
7.(a) Most game playing programs donot save search results from one move to the next. Instead, they
usually start completely afresh whenever it is the machine's turn to move. Why ?
(b) Make the augmented transition network for the following sentence :
"The dog likes a man" explain steps.
Or
8.(a) Describe the STRIPS language for respresenting states, goals and operators within a planning
system.
(b) Give a definition of a plan, a consistent plan and a complete plan.
(c) Describe the initial plan used as a starting point by the partial-order planning algorithm.
(d) Outline the way in whichthe partial-order planning algorithm constructs a plan beginning with
the initial plan. Include in your answer a description of a threat along with an explanation
of how the algorithm can attempt to remove threats by promotion or demotion.
Unit - V
9.(a) Discuss the advantages and shortcomings of probabilistic reasoning.
(b) Explain the differences among the three main styles of learning :
(i) Supervised
(ii) Reinforcement
(iii) Unsupervised
Or
10. Give short definitions of any ten of the following terms :
(i) Circumscription
(ii) Situation Calculus
(iii) Closed world Assumption
(iv) Expert System
(v) Automatic Discovery of Heuristics
(vi) Inter-Wave Search
(vii) Abduction
(ix) Microworld
(x) Maximum Expected Utility
(xi) Intelligent Agent Architecture
(xii) Fuzzy Control
(xiii) Constraint
(xiv)Problem Space(or Search Space)
(xv) Nov-Monotonic Reasoning.
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