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This is a aiml model question paper from the university VTU most of the questions will be asked from this
Typology: Exams
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Time: 03 Hours Max Marks: 100 Note: Answer any FIVE full questions, choosing ONE question from each Module.
MODULE-
1 a. Define Artificial Intelligence and list the task domains of Artificial Intelligence. (10 Marks)
b. Stat e and explain algorithm for Best First Search Algorithm with an example. (10 Marks) OR 2 a. A Water Jug Problem: You are given two jugs, a 4-gallon one and a 3-gallon one, a pump which has unlimited water which you can use to fill the jug, and the ground on which water may be poured. Neither jug has any measuring markings on it. How can you get exactly 2 gallons of water in the 4-gallon jug (i) Write down the production rules for the above problem (ii) Write any one solution to the above problem (10 Marks) b. Elaborate the steps of Simulated Annealing. (10 Marks)
MODULE- 3 a. Describe the issues of Knowledge Representation (10 Marks)
b. Consider the following set of well-formed formulas in predicate logic (i) Man(Marcus) (ii) Pompeian(Marcus) (iii) ∀x: Pompeian(x) → Roman(x) (iv) ruler(Caesar) (v) ∀x: Roman(x) → loyalto(X. Caesar) V hate(x, Caesar) (vi) ∀x :→y: loyalto(x,y) (vii) ∀x :∀ y : man(x) ∧ ruler(y) ∧tryassassinate(x,y) → loyalto(x,y) (viii) tryassassinate (Marcus, Caesar) Convert these into clause form and prove that hate (marcus, Caesar) using resolution proof (10 Marks) OR 4 a. Recall Concept Learning and also Explain hypothesis space of Find-S (05 Marks) b. List out the steps of Candidate Elimination Algorithm. Apply the algorithm to obtain the final version space for the training example Ex. Sky Airtemp Humidity wind Water Forecast Enjoy 1 Sunny Warm Normal Strong Warm Same Yes
2 Sunny Warm High Strong Warm Same Yes 3 Rainy Cold High Strong Warm Change No 4 Sunny Warm High Strong Cool Change Yes
(10 Marks) c. Compare the key differences between Find-S and Candidate Elimination Algorithm. (05 Marks)
.
MODULE- 5 a. Outline the ID3 Decision Tree Learning method (08 Marks)
b. Summarize the appropriate problems for Decision Tree Learning method and also bring out the issues in decision tree learning (08 Marks) c. Construct Decision trees to represent the following Boolean functions (i) A and B (ii) A or [B and C] (iii) [A and B] or [C and D] (04 Marks)
6. a. For the transactions shown in the table compute the following:
(i) Entropy of the collection of transaction records of the table with respect to classification. (ii)What is the information gain of A1 and A2 relative to the transactions of the table? Instance. Classification A1 A 1 + T T 2 + T T 3 - T F 4 + F F 5 - F T 6 - F T (08 Marks) b. Discuss the application of Neural Network which is used for learning to steer an autonomous vehicle. (06 Marks)
Assume K=
Test Example
BMI=43.6, Age=40, Sugar=?
(10 Marks)
BMI Age Sugar 33.6 50 1 26.6 30 0 23.4 40 0 43.1 67 0 35.3 23 1 35.9 67 1 36.7 45 1 25.7 46 0 23.3 29 0 31 56 1