M.Tech AI & ML Semester Exam 2026/2027 – Artificial Intelligence &
Machine Learning Complete Study Guide, Questions and Answers
with Rationales
PART I — ARTIFICIAL INTELLIGENCE FUNDAMENTALS
1. What is the primary objective of Artificial Intelligence?
A. To increase computer storage
B. To build systems capable of performing tasks requiring intelligent
behavior
C. To replace all computer networks
D. To eliminate programming
Answer: B
Rationale: AI focuses on creating systems capable of tasks such as
reasoning, learning, perception, planning, language understanding, and
decision-making.
2. Which of the following is an example of narrow AI?
A. A hypothetical machine with human-level intelligence in every
domain
B. A chess-playing system
C. Human consciousness
D. General human reasoning
Answer: B
Rationale: Narrow AI is designed for specific tasks or domains, such as
chess, recommendation, or image classification.
,3. An intelligent agent primarily:
A. Stores files
B. Perceives its environment and acts upon it
C. Only performs arithmetic
D. Compresses data
Answer: B
Rationale: An intelligent agent receives percepts from an environment
and selects actions to achieve objectives.
4. Which component allows an agent to receive information from its
environment?
A. Actuator
B. Sensor
C. Compiler
D. Optimizer
Answer: B
Rationale: Sensors provide perceptual information, while actuators
execute actions.
5. A rational agent chooses an action that:
A. Is always random
B. Maximizes expected performance based on available information
C. Requires human approval
D. Minimizes computation regardless of outcome
Answer: B
,Rationale: Rationality means selecting actions expected to maximize
the performance measure given the available information.
6. Which search strategy uses a FIFO queue?
A. DFS
B. BFS
C. Hill climbing
D. Genetic search
Answer: B
Rationale: Breadth-first search expands nodes level by level using a
FIFO queue.
7. Which search strategy generally uses a LIFO structure?
A. BFS
B. DFS
C. Uniform-cost search
D. A*
Answer: B
Rationale: Depth-first search explores the deepest available node first,
commonly implemented using a stack.
8. A* search evaluates nodes using:
A. f(n) = g(n) − h(n)
B. f(n) = g(n) + h(n)
, C. f(n) = g(n) × h(n)
D. f(n) = h(n) − g(n)
Answer: B
Rationale: A* combines the cost already incurred, g(n), with the
estimated remaining cost, h(n).
9. What property of a heuristic helps A* guarantee optimality under
standard conditions?
A. Randomness
B. Admissibility
C. Large memory consumption
D. High branching factor
Answer: B
Rationale: An admissible heuristic never overestimates the true
remaining cost.
10. Which problem is particularly suited to a constraint satisfaction
formulation?
A. Sudoku
B. Image compression
C. Sorting an array
D. Multiplication
Answer: A
Rationale: Sudoku consists of variables, domains, and constraints,
making it a classic CSP.
Machine Learning Complete Study Guide, Questions and Answers
with Rationales
PART I — ARTIFICIAL INTELLIGENCE FUNDAMENTALS
1. What is the primary objective of Artificial Intelligence?
A. To increase computer storage
B. To build systems capable of performing tasks requiring intelligent
behavior
C. To replace all computer networks
D. To eliminate programming
Answer: B
Rationale: AI focuses on creating systems capable of tasks such as
reasoning, learning, perception, planning, language understanding, and
decision-making.
2. Which of the following is an example of narrow AI?
A. A hypothetical machine with human-level intelligence in every
domain
B. A chess-playing system
C. Human consciousness
D. General human reasoning
Answer: B
Rationale: Narrow AI is designed for specific tasks or domains, such as
chess, recommendation, or image classification.
,3. An intelligent agent primarily:
A. Stores files
B. Perceives its environment and acts upon it
C. Only performs arithmetic
D. Compresses data
Answer: B
Rationale: An intelligent agent receives percepts from an environment
and selects actions to achieve objectives.
4. Which component allows an agent to receive information from its
environment?
A. Actuator
B. Sensor
C. Compiler
D. Optimizer
Answer: B
Rationale: Sensors provide perceptual information, while actuators
execute actions.
5. A rational agent chooses an action that:
A. Is always random
B. Maximizes expected performance based on available information
C. Requires human approval
D. Minimizes computation regardless of outcome
Answer: B
,Rationale: Rationality means selecting actions expected to maximize
the performance measure given the available information.
6. Which search strategy uses a FIFO queue?
A. DFS
B. BFS
C. Hill climbing
D. Genetic search
Answer: B
Rationale: Breadth-first search expands nodes level by level using a
FIFO queue.
7. Which search strategy generally uses a LIFO structure?
A. BFS
B. DFS
C. Uniform-cost search
D. A*
Answer: B
Rationale: Depth-first search explores the deepest available node first,
commonly implemented using a stack.
8. A* search evaluates nodes using:
A. f(n) = g(n) − h(n)
B. f(n) = g(n) + h(n)
, C. f(n) = g(n) × h(n)
D. f(n) = h(n) − g(n)
Answer: B
Rationale: A* combines the cost already incurred, g(n), with the
estimated remaining cost, h(n).
9. What property of a heuristic helps A* guarantee optimality under
standard conditions?
A. Randomness
B. Admissibility
C. Large memory consumption
D. High branching factor
Answer: B
Rationale: An admissible heuristic never overestimates the true
remaining cost.
10. Which problem is particularly suited to a constraint satisfaction
formulation?
A. Sudoku
B. Image compression
C. Sorting an array
D. Multiplication
Answer: A
Rationale: Sudoku consists of variables, domains, and constraints,
making it a classic CSP.
