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Posted By: Ramya Member Level: Silver Posted Date: 16 Dec 2007
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2007 Anna University M.C.A Agent Based Intelligent System Question paper
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M.C.A DEGREE EXAMINATION,NOVEMBER/DECEMBER 2007
Elective
MC 1636 — AGENT BASED INTELLIGENT SYSTEM
(REGULATION 2005)
Time:THREE HOURS Maximum:100 marks
Answer ALL questions
PART A-(10 x 2=20 marks)
1. Define Agent.Explain the functionalities of Agent program.
2. State a problem where best first search is worse than simple
breadth first search.
3. List down the different types of knowledge representation techniques.
4. Give the characteristics of knowledge based agents.
5. Define state space search.
6. List the funcytionalities of continuous planning agent.
7. Define Baye’s rule.
8. Define dempster Shafer theory.
9. Give the concept behind reinforcement learning.
10. What is use of augmented grammars in Natural Language Processing?
PART B-(5 x 16=80 marks)
11. (a) Explain in detail the structure of different types of agents. (16)
Or
(b) (i) Explain satisfaction problem with an example. (8)
(ii) Explain A* algorithm. (8)
12. (a) (i) Explain unification algorithm. (6)
(ii) Consider the following sentences:
• The members of Elm St. Bridge Club are Joe,Sally,Bill and
Ellen
• Joe is married to Sally
• Bill is Ellen’s brother
• The spouse of every married person in the is also
In the club
? Last meeting of the club was at Joe’s house
- Translate these sentences into predicate form.
- Prove by resolution
? Last meeting of the club was at Slly’s house
? Ellen is not married. (10)
Or
(b) Explain partial order planning approach with an example. (16)
13. (a) Explain the partial order planning approach with an example. (16)
Or
(b) Write short notes on:
-Conditional planning . (8)
-Multiagent planning. (8)
14. (a)(i) Explain the method of acting with uncertainty using Bayesian
network. (10)
(ii) Why the axioms of probability are reasonable? (6)
Or
(b) Explain the concept of inference in temporal models. (16)
15. (a) Explain in detail on different types of statistical learning methods.
(16)
Or
(b) Explain the various stages involved in analyzing a sentence in Natural Language Processing. (16)
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