STUPIDSID
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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