Download AKTU B-Tech 8th Sem 2014-15 ECS 801 Artificial Intelligence Question Paper

Download AKTU (Dr. A.P.J. Abdul Kalam Technical University (AKTU), formerly Uttar Pradesh Technical University (UPTU) B-Tech 8th Semester (Eight Semester) 2014-15 ECS 801 Artificial Intelligence Question Paper

Prihted Pages : 3 ' '
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(Following Paper ID and Roll No. to be ?lled in your Answer Book)
PAPER ID : 110801
Roll No.
B. Tech. _
'(SEM. VIII) THEORY EXAMINATION, 2014-15
? ARTIFICIAL INTELLIGENCE
Time : 3 Hours] [Total Marks : 100
Note: Attempt all questions.
1 Attempt any four parts of the following: 5X4=20
(a) Explain the term arti?cial intelligence. How does
it di?'er from general intelligence?
(b) Describe the role of di??erent disciplines in the
emergence of arti?cial intelligence as a new
science.
(c) What is an agent program? De?cribe the structure
of a typical agent program.
(d) List some of the state?of-the-art applications of
the arti?cial intelligence.
(e) Describe the role of arti?cial intelligence in
computer vision.
(t) How does a language processing system work.
' 110801] . 1 [Contd...

(a)
(b)
(e)
(a)
(b)
(o)
(a)
(b)
(0)
110801]
Attempt any two parts of the following:
Attempt any two parts of the following:
Attempt any two parts of the following:
10X2=20
Descn?be the role of arti?cial intelligence in search.
Illustrate your answer using 8-queens problem.
Explain BFS and DFS search techniques in detail.
Describe A" search technique, Prove that A* is
complete and optimal.
l 0 x2=20
Determine whether the following argument is valid.
"If I work whole night on this problem, then I
can solve it. If I solve the problem, then I will
understand the topic. Therefore, I will work whole
night on this problem, then I will understand the
topic." _
De?ne Hidden Markov Model (HMM). Illustrate
how HMMs are used for speech recognition.
Describe Bayesian networks. How does the
Bayesian networks are the powerful representation
for uncertainty knowledge?
What do mean by machine leaming? Illustrate any
two supervised learning techniques.
Explain decision trees learning technique using a
suitable example.
Elaborate Naive Bayes model in detail.
2 [ Contd...
10x2=2o -
(a)
(b)
(C)
(d)
(e)
(1)
110301]
Write short notes on any four of the following: 5X4=20
Pattern Recognition System
P?noiple Component analysis
' Discriminant Component Analysis
Clusteu'ng
Support vector machine
Arti?cial, neural networks
3 I [12450]