MCS-224 Solved Assignment 2025

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MCS-224 Solved Assignment 2025 Available

Q1: Compare ANI, AGI and ASI, in context of AI. Also, discuss the major applications of AI.
Q2: What is Turing Test? What is the Criticism to the Turing Test?
Q3: Compare Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).
Q4: What are Intelligent agents in AI? Briefly discuss the properties of Agents.
Q5: Find the minimum cost path for the 8-puzzle problem, where the start and goal state are given as follows:
Start State Goal State
Q6: Consider the following Minimax game tree search in which root is maximizing node and children are
visited from left to right. Find the value of the root node of the game tree?
1 2 3
8 4
7 6 5
2 8 1
4 3
7 6 5
Q7: Define a frame for the entity date which consists of day, month and year. each of which is a number
with restrictions which are well-known. Also, a procedure named compute-day-of-week is already
defined.
Q8: In a class, three students tossed one coins (one each) for 3 times. Write down all the possible outcomes
which can be obtained in this experiment. What is the probability of getting 2 or more than 2 heads at a
time? Also find the probability of getting three tails at a time.
Q9: Briefly discuss the various Ensemble Methods.
Q10: Explain K-Nearest Neighbour (K-NN) classification algorithm with the help of a suitable example
Q11: Using the following training dataset, apply Naïve Bayes classification algorithm to find the class of an
unknown sample X = < Rainy, Cool, High, False >
S. No. Outlook Temperature Humidity Windy Play Golf/Class
0 Rainy Hot High False No
1 Rainy Hot High True No
2 Overcast Hot High False Yes
3 Sunny Mild High False Yes
4 Sunny Cool Normal False Yes
5 Sunny Cool Normal True No
6 Overcast Cool Normal True Yes
7 Rainy Mild High False No
8 Rainy Cool Normal False Yes
9 Sunny Mild Normal False Yes
10 Rainy Mild Normal True Yes
11 Overcast Mild High True Yes
12 Overcast Hot Normal False Yes
13 Sunny Mild High True No
5
Q12: Explain working of SVM algorithm with the help of a suitable example.
Q13: Consider the following set of data points (Year of experience salary). Find the 2nd order polynomial
y=𝑎0 + 𝑎1𝑥i + 𝑎2 𝑥i2, and using polynomial regression determine the salary when year of experience is
10.
Years of Experience (X) Salary (Y) in Dollar
1 50,000
2 55,000
3 65,000
4 80,000
5 110,000
6 150,000
7 200,000
Q14: Write Back Propagation algorithm, and showcase its execution on a neural network of your choice
(make suitable assumptions if any)
Q15: Consider the two-dimensional patterns (2, 2), (3, 6), (4, 4), (5, 6), (6, 7), (7, 8), (8, 8) and (9, 10).
Using the PCA Algorithm, calculate the primary component.
Q16: Compute the Linear Discriminant projection for the following two-dimensional dataset
X1 = (x1, x2) = {(4,2), (2,1), (2,4), (3,5), (4,5)} and X2 = (x1, x2) = {(9, 9), (6, 9), (9, 6), (8, 7),
(10, 9)}