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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