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 | May, 2017 | |
City, State | tamil nadu, karaikudi |
Question Paper
DISTANCE EDUCATION
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
MAY 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. Give a brief note on Rational Agents.
2. What is the need for optimal decision in games? Explain.
3. Write short notes on Resolution Strategies.
4. Explain the State- Space search.
5. Give a brief note on Conditional Planning.
6. Explain the Utility Theorem.
7. Bring out the significance of Knowledge in Learning.
8. Give a brief note on Reinforcement Learning.
Sub. Code
603
DE-703
2
Ws9
PART B — 15 60 marks)
Answer any FOUR questions.
9. Give a detailed description on agents and the nature of
environments.
10. Illustrate the concept of problem solving with an
example.
11. Describe the syntax and semantics of First-order logic.
12. Give a detailed note on forward chaining.
13. Explain the planning problem.
14. Give a detailed description on Bayesian networks.
15. Bring out the significance of communication for agents.
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
MAY 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. Give a brief note on Rational Agents.
2. What is the need for optimal decision in games? Explain.
3. Write short notes on Resolution Strategies.
4. Explain the State- Space search.
5. Give a brief note on Conditional Planning.
6. Explain the Utility Theorem.
7. Bring out the significance of Knowledge in Learning.
8. Give a brief note on Reinforcement Learning.
Sub. Code
603
DE-703
2
Ws9
PART B — 15 60 marks)
Answer any FOUR questions.
9. Give a detailed description on agents and the nature of
environments.
10. Illustrate the concept of problem solving with an
example.
11. Describe the syntax and semantics of First-order logic.
12. Give a detailed note on forward chaining.
13. Explain the planning problem.
14. Give a detailed description on Bayesian networks.
15. Bring out the significance of communication for agents.
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- .net frame works
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- accounting and financial management
- agent based intelligent system
- c-sharp (c#)
- communication skills
- compiler design
- computer applications
- computer networks
- data mining and warehousing
- data warehousing and mining
- distributed computing
- image processing and analysis
- internet programming
- lab : vi — algorithm and shell programming
- lab v — rdbms
- lab vii –– internet programming
- lab viii — network lab
- lab x — compiler design
- lab–ix : visual c++
- middleware technology
- mobile communications
- multimedia systems
- multimedia tools lab
- network lab
- neural networks
- object oriented analysis and design
- open source architecture
- open source programming lab
- operating systems
- rdbms
- resource management techniques
- software engineering
- software project management
- unix and shell programming
- visual programming
- visual programming lab
- web technology
- web technology lab