Exam Details
Subject | agent based intelligent system | |
Paper | ||
Exam / Course | m.c.a./ m.c.a.(lateral) | |
Department | ||
Organization | Alagappa University Distance Education | |
Position | ||
Exam Date | December, 2017 | |
City, State | tamil nadu, karaikudi |
Question Paper
DISTANCE EDUCATION
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
DECEMBER 2017.
Sixth Semester
AGENT BASED INTELLIGENT SYSTEM
(2010 Academic Year onwards)
Time Three hours Maximum 100 marks
PART A — × 8 40 marks)
Answer any FIVE questions.
1. List out the various searching strategy.
2. Write a brief note on alpha beta pruning that is used in
gaming.
3. Discuss forward and backward chaining.
4. Bring out the significance of logical agents.
5. Describe the partial order planning approach with an
example.
6. Write a brief note on multiagent planning.
7. Explain how vagueness is represented using fuzzy logic.
8. Discuss the reinforcement learning.
Sub. Code
603
DE-3005
2
wk4
PART B — × 15 60 marks)
Answer any FOUR questions.
9. Explain about the different Heuristic Search techniques.
10. Discuss the different issues in knowledge representation.
11. Explain the syntax and semantics used in first order
logic.
12. Explain how planning is carried out using state space
research.
13. Explain the semantics of Bayesian networks.
14. With suitable examples Explain complex decision
making.
15. Explain the different statistical learning methods.
———————
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
DECEMBER 2017.
Sixth Semester
AGENT BASED INTELLIGENT SYSTEM
(2010 Academic Year onwards)
Time Three hours Maximum 100 marks
PART A — × 8 40 marks)
Answer any FIVE questions.
1. List out the various searching strategy.
2. Write a brief note on alpha beta pruning that is used in
gaming.
3. Discuss forward and backward chaining.
4. Bring out the significance of logical agents.
5. Describe the partial order planning approach with an
example.
6. Write a brief note on multiagent planning.
7. Explain how vagueness is represented using fuzzy logic.
8. Discuss the reinforcement learning.
Sub. Code
603
DE-3005
2
wk4
PART B — × 15 60 marks)
Answer any FOUR questions.
9. Explain about the different Heuristic Search techniques.
10. Discuss the different issues in knowledge representation.
11. Explain the syntax and semantics used in first order
logic.
12. Explain how planning is carried out using state space
research.
13. Explain the semantics of Bayesian networks.
14. With suitable examples Explain complex decision
making.
15. Explain the different statistical learning methods.
———————
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