M.Tech Artificial Intelligence & Machine Learning
Exam 2026/2027 – Practice Questions & Answers
with Rationales
SECTION 1 — ARTIFICIAL INTELLIGENCE FUNDAMENTALS
1. What is the primary goal of Artificial Intelligence?
A. Increase storage capacity
B. Create systems capable of intelligent behavior
C. Replace computer networks
D. Eliminate algorithms
Answer: B
Rationale: AI aims to develop systems capable of tasks involving
reasoning, learning, perception, planning, and decision-making.
2. Which of the following is an example of narrow AI?
A. A hypothetical human-level general intelligence
B. A chess-playing program
C. Human consciousness
D. General-purpose human reasoning
Answer: B
Rationale: Narrow AI is designed to perform specific tasks rather than
general intelligence across domains.
3. An intelligent agent primarily:
A. Stores information
B. Perceives its environment and takes actions
,C. Compiles programs
D. Controls databases
Answer: B
Rationale: Agents use sensors to perceive environments and actuators
to perform actions.
4. Which component allows an agent to perceive its environment?
A. Actuator
B. Sensor
C. Compiler
D. Optimizer
Answer: B
Rationale: Sensors collect information from the environment.
5. A rational agent selects an action that:
A. Is always random
B. Maximizes expected performance
C. Requires human intervention
D. Minimizes computation regardless of outcome
Answer: B
Rationale: Rational agents select actions expected to maximize their
performance measure.
6. Which search algorithm uses a FIFO queue?
A. DFS
B. BFS
C. Hill climbing
D. Simulated annealing
,Answer: B
Rationale: Breadth-first search uses a FIFO queue and explores nodes
level by level.
7. Which search algorithm is commonly implemented using a stack?
A. BFS
B. DFS
C. Uniform-cost search
D. A*
Answer: B
Rationale: Depth-first search explores the deepest available node first
and uses stack-like behavior.
8. The evaluation function for A* is:
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. An admissible heuristic:
A. Always overestimates cost
B. Never overestimates the true cost
C. Is always zero
D. Is always exact
Answer: B
Rationale: Admissibility means the heuristic provides an optimistic
estimate.
, 10. Which is a classic constraint satisfaction problem?
A. Sudoku
B. File compression
C. Matrix multiplication
D. Sorting
Answer: A
Rationale: Sudoku contains variables, domains, and constraints.
11. In a CSP, a domain specifies:
A. Possible values of a variable
B. The number of processors
C. The search algorithm
D. The objective function
Answer: A
Rationale: A variable's domain contains the values it can legally take.
12. The Minimum Remaining Values heuristic selects:
A. The variable with the largest domain
B. The variable with the fewest legal values
C. A random variable
D. The most recently assigned variable
Answer: B
Rationale: MRV prioritizes the most constrained variable.
13. Knowledge representation allows an AI system to:
A. Represent and reason about knowledge
B. Increase CPU frequency
C. Compress images
D. Increase network bandwidth
Exam 2026/2027 – Practice Questions & Answers
with Rationales
SECTION 1 — ARTIFICIAL INTELLIGENCE FUNDAMENTALS
1. What is the primary goal of Artificial Intelligence?
A. Increase storage capacity
B. Create systems capable of intelligent behavior
C. Replace computer networks
D. Eliminate algorithms
Answer: B
Rationale: AI aims to develop systems capable of tasks involving
reasoning, learning, perception, planning, and decision-making.
2. Which of the following is an example of narrow AI?
A. A hypothetical human-level general intelligence
B. A chess-playing program
C. Human consciousness
D. General-purpose human reasoning
Answer: B
Rationale: Narrow AI is designed to perform specific tasks rather than
general intelligence across domains.
3. An intelligent agent primarily:
A. Stores information
B. Perceives its environment and takes actions
,C. Compiles programs
D. Controls databases
Answer: B
Rationale: Agents use sensors to perceive environments and actuators
to perform actions.
4. Which component allows an agent to perceive its environment?
A. Actuator
B. Sensor
C. Compiler
D. Optimizer
Answer: B
Rationale: Sensors collect information from the environment.
5. A rational agent selects an action that:
A. Is always random
B. Maximizes expected performance
C. Requires human intervention
D. Minimizes computation regardless of outcome
Answer: B
Rationale: Rational agents select actions expected to maximize their
performance measure.
6. Which search algorithm uses a FIFO queue?
A. DFS
B. BFS
C. Hill climbing
D. Simulated annealing
,Answer: B
Rationale: Breadth-first search uses a FIFO queue and explores nodes
level by level.
7. Which search algorithm is commonly implemented using a stack?
A. BFS
B. DFS
C. Uniform-cost search
D. A*
Answer: B
Rationale: Depth-first search explores the deepest available node first
and uses stack-like behavior.
8. The evaluation function for A* is:
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. An admissible heuristic:
A. Always overestimates cost
B. Never overestimates the true cost
C. Is always zero
D. Is always exact
Answer: B
Rationale: Admissibility means the heuristic provides an optimistic
estimate.
, 10. Which is a classic constraint satisfaction problem?
A. Sudoku
B. File compression
C. Matrix multiplication
D. Sorting
Answer: A
Rationale: Sudoku contains variables, domains, and constraints.
11. In a CSP, a domain specifies:
A. Possible values of a variable
B. The number of processors
C. The search algorithm
D. The objective function
Answer: A
Rationale: A variable's domain contains the values it can legally take.
12. The Minimum Remaining Values heuristic selects:
A. The variable with the largest domain
B. The variable with the fewest legal values
C. A random variable
D. The most recently assigned variable
Answer: B
Rationale: MRV prioritizes the most constrained variable.
13. Knowledge representation allows an AI system to:
A. Represent and reason about knowledge
B. Increase CPU frequency
C. Compress images
D. Increase network bandwidth
