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Solve any one question from Q.1(a,b,c) & Q.2(a,b,c)
1(a)
Give any three examples of agent types and their PAGE descriptions.
6 M
1(b)
Define purning. Explain alpha beta purning with its effectiveness.
8 M
1(c)
Explain backward chaining algorithms with suitable example.
6 M
2(a)
Explain different uninformed searching stratgies with respect to different parameters.
6 M
2(b)
Explain back tracking search and local search of CSP with algorithm.
8 M
2(c)
What is knowledge enginnering? Explain knowledge enginerring Vs. Programming.
6 M
Solve any one question from Q.3(a,b) & Q.4(a,b)
3(a)
What is reinforcement learning? Explain passive & active reinforcement learning in details.
10 M
3(b)
How performance of learning algorithm is assessed?
8 M
4(a)
What are the different learning method? Explain any one in detail.
10 M
4(b)
Explain statistical learning methods with example.
8 M
Solve any one question from Q.5(a,b) & Q.6(a,b)
5(a)
Explain expert system constituents with an example of "Medical Diagnosis System".
8 M
5(b)
Explain Perception confined to Vision and Speech recognition.
8 M
6(a)
Explain Waltz algorithm with example. What are its limitations?
8 M
6(b)
Give detailed architecture of Expert system.
8 M
Solve any one question from Q.7(a,b) & Q.8(a,b)
7(a)
What is Natural Language Understanding? Explain it detail.
8 M
7(b)
Explain the Syntactic analysis with suitable Example.
8 M
8(a)
Explain in details "Probabilistic language models".
8 M
8(b)
Explain the Semantic interpretation with suitable example.
8 M
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