Artificial Intelligence MCQs with Answers
Practice important Artificial Intelligence MCQs with answers and explanations.
Chapter: 11
Q341:
In Genetic Algorithms, which individuals are more likely to survive and reproduce?
A. Random individuals
B. Better adapted individuals
C. Weak individuals
D. Oldest individuals
Correct Answer:
B
Chapter: 11
Q342:
Which of the following best defines the "fitness" concept in Genetic Algorithms?
A. Number of mutations
B. Quality of solutions
C. Number of offspring
D. Age of individual
Correct Answer:
B
Chapter: 11
Q343:
What is the role of the population in Genetic Algorithms?
A. Single solution to problem
B. Multiple candidate solutions
C. Mutation only
D. Inheritance only
Correct Answer:
B
Chapter: 11
Q344:
The main goal of hill climbing in search algorithms is to:
A. Reach the bottom of the hill
B. Reach the top of the hill
C. Maintain the current position
D. Avoid movement
Correct Answer:
B
Chapter: 11
Q345:
Genetic Algorithms produce the next generation using:
A. Only mutation
B. Only inheritance
C. Inheritance and mutation
D. Random guessing
Correct Answer:
C
Chapter: 12
Q346:
In the GA problem of 32-bit computer words, what is the target string composed of?
A. All zeros
B. All ones
C. Alternating bits
D. Random bits
Correct Answer:
B
Chapter: 12
Q347:
How many computer words are initially created in the 32-bit GA problem?
A. 50
B. 10
C. 100
D. 32
Correct Answer:
C
Chapter: 12
Q348:
What does the GA algorithm count in each word during evaluation?
A. Number of zeros
B. Number of ones
C. Number of toggled bits
D. Number of mutations
Correct Answer:
B
Chapter: 12
Q349:
In the 32-bit word problem, how many words with the most 1s are kept after evaluation?
A. 5
B. 10
C. 20
D. 50
Correct Answer:
B
Chapter: 12
Q350:
What operation is performed to generate new words from each existing word in the mutation-only GA approach?
A. Toggle a random bit
B. Swap two bits
C. Set all bits to 1
D. Reverse bits
Correct Answer:
A
Chapter: 12
Q351:
Mutation in GA can be described as:
A. Swapping chromosomes
B. Crossing over bits
C. Flipping bits at random
D. Cloning individuals
Correct Answer:
C
Chapter: 12
Q352:
The evaluation function in GA measures:
A. How many mutations occurred
B. How good a solution is
C. How many bits are zeros
D. How many generations passed
Correct Answer:
B
Chapter: 12
Q353:
If no perfect solution is found within the time limit, GA presents:
A. The worst solution
B. The first solution
C. The best possible solution
D. The last solution
Correct Answer:
C
Chapter: 12
Q354:
In Problem 2 (polynomial fitting), the formula used to fit data points is:
A. y = mx + c
B. y = ax^2 + bx + c
C. y = mx^2 + c
D. y = mx^2 + bx + c
Correct Answer:
A
Chapter: 12
Q355:
In Problem 2, what are the unknowns in the polynomial fitting GA problem?
A. m and c
B. a and b
C. x and y
D. m and b
Correct Answer:
B
Chapter: 12
Q356:
How is the “badness” of a solution in polynomial fitting GA calculated?
A. Sum of (actual y – predicted y)
B. Sum of (predicted y – actual y)^2
C. Sum of (actual y – predicted y)^2
D. Sum of (x – y)^2
Correct Answer:
C
Chapter: 12
Q357:
In the polynomial fitting example, if m=5 and c=7, what is the predicted y when x=1?
A. 5
B. 7
C. 12
D. 35
Correct Answer:
C
Chapter: 12
Q358:
What does the GA algorithm keep after evaluating the badness of arrays in polynomial fitting?
A. Best arrays with high badness
B. Worst arrays
C. Best arrays with low badness
D. Random arrays
Correct Answer:
C
Chapter: 12
Q359:
How many new arrays are generated from the kept arrays in polynomial fitting GA?
A. 5
B. 9
C. 10
D. None
Correct Answer:
B
Chapter: 12
Q360:
What is the representation of the array [1, 3] in binary (as per example)?
A. [011 011]
B. [001 011]
C. [010 010]
D. [100 011]
Correct Answer:
B