B.Sc. (Computer Science) Sem 5 Artificial Intelligence 2023-24 Question Paper - Mumbai University | munotes

Questions asked in this paper

• N.B. (1) All questions are compulsory. (2) Figures to the right indicate marks. (3) Illustrations, in-depth answers and diagrams will be appreciated. (4) Mixing of sub-questions is not allowed.

SECTION I - Q.1 (Attempt ANY FOUR from the following) 20 Marks

1. (a) What is PEAS? Give a PEAS description for playing a tennis match and vacuum cleaner problem.
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2. (b) Define AI? Explain any 2 foundations of AI.
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3. (c) Explain the 8-Queens Problem and write the States, Initial state, Actions, Transition Model, Goal state & Path cost to formulate it.
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4. (d) Explain Depth First Strategy along with pseudocode.
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5. (e) Write a short note on model based agent.
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6. (f) Find the optimal path & path cost for the following graph using A* search algorithm. (S is a Start state & G is a Goal State) [Directed graph: S to A cost 1, S to G cost 10; A to B cost 2, A to C cost 1; B to D cost 5; C to D cost 3, C to G cost 4; D to G cost 2. Heuristic h(n): S 5, A 3, B 4, C 2, D 6, G 0.]
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SECTION II - Q.2 (Attempt ANY FOUR from the following) 20 Marks

1. (a) Describe knowledge representation. Explain frame representation technique of knowledge representation in detail.
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2. (b) Write a note on Multilayer Feed Forward Neural Network.
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3. (c) Explain the concept of Overfitting and Underfitting of model.
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4. (d) What is Regression? Explain Simple Linear Regression with example.
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5. (e) Define Ensemble Learning. Explain Boosting technique in detail.
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6. (f) Explain KNN classifier with example.
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SECTION III - Q.3 (Attempt ANY FOUR from the following) 20 Marks

1. (a) Write a short note on Q learning.
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2. (b) Differentiate between reinforcement and unsupervised learning.
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3. (c) For the given transaction dataset [100: Bread, Cheese; 200: Bread, Cheese, Juice; 300: Bread, Milk; 400: Cheese, Juice, Milk] calculate the following: (i) Support(bread) (ii) Support(bread->milk) (iii) Confidence(bread->cheese) (iv) Confidence(bread->milk) (v) Lift(bread->cheese)
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4. (d) Explain Hidden Markov Model in detail.
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5. (e) What is Clustering? Explain with example.
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6. (f) Write a short note on association rule mining.
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SECTION IV - Q.4 (Attempt ANY FIVE from the following) 15 Marks

1. (a) Explain Turing Test Approach in AI.
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2. (b) Explain Deterministic vs Stochastic Task Environment with suitable example.
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3. (c) Write a note on Active Reinforcement learning.
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4. (d) Explain Bellman Equation in detail.
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5. (e) What is the role of Reasoning in AI?
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6. (f) Explain the concept of gradient descent.
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Read from the scan above, so a character or two may differ. The scan is the original.