 MORE IN Smart System Design and Applications
SPPU Computer Engineering (Semester 7)
Smart System Design and Applications
December 2016
Total marks: --
Total time: --
INSTRUCTIONS
(1) Assume appropriate data and state your reasons
(2) Marks are given to the right of every question
(3) Draw neat diagrams wherever necessary

Solve any one question Q.1(a,b,c) and Q.2(a, b,c)
1(a) Explain the architecture of a learning agent and its components.
8 M
1(a) Explain the architecture of a learning agent and its components.
8 M
1(b) Explain AO* algorithm with an example.
6 M
1(b) Explain AO* algorithm with an example.
6 M
1(c) Explain the procedure for conversion of FOL to CNF with example.
6 M
1(c) Explain the procedure for conversion of FOL to CNF with example.
6 M

2(a) Defien search problem. Solve 8 queen problem as state space search problem.
8 M
2(a) Defien search problem. Solve 8 queen problem as state space search problem.
8 M
2(b) Explain MINI-MAX search algorithm for solving any game.
6 M
2(b) Explain MINI-MAX search algorithm for solving any game.
6 M
2(c) Write a short note on planning graphs.
6 M
2(c) Write a short note on planning graphs.
6 M

Solve any one question.Q.3(a,b)and Q.4(a,b)
3(a) Explain the Baye's rule with a suitable example.
4 M
Solve any one question.Q3(a,b) Q4(a,b)
3(a) Explain the Baye's rule with a suitable example.
4 M
3(b) What is Bayesian Networks? What we are achieving through it ? Explain it's at least TWO areas of application.
8 M
3(b) What is Bayesian Networks? What we are achieving through it ? Explain it's at least TWO areas of application.
8 M

4(a) How to compute an interface in temporal model and Hidden Markov Model? Explain in brief.
6 M
4(a) How to compute an interface in temporal model and Hidden Markov Model? Explain in brief.
6 M
4(b) Explain the construction of Dynamic Bayesian Networks with a suitable example.
6 M
4(b) Explain the construction of Dynamic Bayesian Networks with a suitable example.
6 M

Solve any one question.Q.5(a,b)and Q.6(a,b)
5(a) Differntiate supervised unsupervised, semi-supervised models in learning approach.
6 M
Solve any one question.Q5(a,b) Q6(a,b)
5(a) Differntiate supervised unsupervised, semi-supervised models in learning approach.
6 M
5(b) Explain any ONE learning approach in building smart system.
6 M
5(b) Explain any ONE learning approach in building smart system.
6 M

6(a) Write a short note on Artifical Networks.
6 M
6(a) Write a short note on Artifical Networks.
6 M
6(b) Explain Non-parametric models.
6 M
6(b) Explain Non-parametric models.
6 M

Solve any one question.Q.7(a,b) and Q.8(a,b)
7(a) Explain different techniques for speech recognition and object recognition.
6 M
Solve any one question.Q7(a,b) Q8(a,b)
7(a) Explain different techniques for speech recognition and object recognition.
6 M
7(b) Explain the method for object recognition by appearance.
6 M
7(b) Explain the method for object recognition by appearance.
6 M

8(a) What is meant by argumented grammar and semantic interpretation? Explain with example.
6 M
8(a) What is meant by argumented grammar and semantic interpretation? Explain with example.
6 M
8(b) How Robot will perceive the information? Explain with example.
6 M
8(b) How Robot will perceive the information? Explain with example.
6 M

Solve any one question.Q.9(a,b)and Q.10(a,b)
9(a) Describe the basis of Utility Theory with utility functions.
6 M
Solve any one question.Q9(a,b) Q10(a,b)
9(a) Describe the basis of Utility Theory with utility functions.
6 M
9(b) How knowledge can be representation? Explain with example.
8 M
9(b) How knowledge can be representation? Explain with example.
8 M

10(a) What is Ontology ? How it is used to represent the inforation? Explain with example.
6 M
10(a) What is Ontology ? How it is used to represent the inforation? Explain with example.
6 M
10(b) Explain 'Internet Shopping World' example with various agents and their usage.
8 M
10(b) Explain 'Internet Shopping World' example with various agents and their usage.
8 M

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