CS9304 - CS481 - Artificial Intelligence - April May 2014

Anna University CS9304 - CS481 Artificial Intelligence April may 2014 question paper, Computer Science and Engineering (CSE), Fifth Semester, Regulation 2008

Exam	B.E/B.Tech. (Full Time) DEGREE END SEMESTER EXAMINATIONS
Academic Year	April May 2014
Subject Code	CS9304/CS481
Subject Name	Artificial Intelligence
Branch	Computer Science and Engineering
Semester	Fifth Semester
Regulation	2008

B.E / B.Tech. (Full Time) DEGREE END SEMESTER EXAMINATIONS, APRIL / MAY 2014

Computer Science and Engineering

Fifth Semester

CS9304/CS481 ARTIFICIAL INTELLIGENCE

(Regulations 2008)

Time : 3 Hours                      Answer A L L Questions                Max. Marks 100

PART-A (10 x 2 = 20 Marks)

1. Define: Agent

2. What are the key features and limitations of Depth First Search?

3. What is a constraint satisfaction problem?

4. How chance nodes are helpful?

5. Represent few properties of categories.

6. Give the axioms of probability.

7. What is inductive learning?

8. What is Okhams razor?

9. How to overcome the ambiguity in natural language?

10. What is localization? Give the techniques available for it.

Part-B (5* 16 = 80 Marks)

11. (i) Discuss about the various kinds of agents and their properties with neat diagram. (10)

(ii) How to avoid repeated search? (6)

12. a) i) Prove that A* search technique is optimal and complete. (10)

ii) Compare and contrast Hill climbing with simulated annealing search. (6)

(OR)

b) i) Describe backtracking search for the constraint satisfaction problem? (8)

ii) With a neat diagram, explain Alpha-beta pruning method. (8)

13. a) i) Represent the following sentences in First Order Logic. (10)

a) Parent and child are inverse relations.

b) Two sets are equal if and only if each is a subset of the other.

c) Connected is a commutative predicate

d) Every student who takes French passes it.

e) No person buys an expensive policy

ii) Write short notes on: Backward chaining. (6)

(OR)

b) i) Discuss about. Mental events and mental objects. (8)

ii) Describe Truth Maintenance systems in detail. (8)

14. a) i) Present the importance of Decision tree learning and Construct decision tree for the given problem. (16)

(OR)

b) i) With neat algorithms, explain Passive Reinforcement Learning in detail. (16)

15. a) i) Explain the component steps of communication in detail. (10)

ii) Write short notes on : Syntactic Analysis. (6)

(OR)

b) Write short notes on:

i) Image Processing (8)

ii) Robotic Perception (8)

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