Artificial Intelligence MCQs with Answers
Practice important Artificial Intelligence MCQs with answers and explanations.
Chapter: 9
Q261:
In Best First Search, the selection of the next node is based on ______.
A. random choice
B. least cost
C. greatest depth
D. best available heuristic
Correct Answer:
D
Chapter: 9
Q262:
Best First Search can sometimes reduce search time because it uses _______.
A. exhaustive methods
B. random guessing
C. heuristics to guide search
D. backtracking
Correct Answer:
C
Chapter: 9
Q263:
Which of the following is a major limitation of heuristic-based searches?
A. They are too slow
B. They require exact algorithms
C. They do not guarantee optimal solutions
D. They can't solve puzzles
Correct Answer:
C
Chapter: 9
Q264:
Which method attempts to find all possible solutions and then chooses the best one?
A. Best First Search
B. Beam Search
C. British Museum Procedure
D. A* Search
Correct Answer:
C
Chapter: 9
Q265:
The British Museum Procedure is analogous to which of the following?
A. Greedy Search
B. Brute Force Search
C. Backtracking
D. Optimal Search
Correct Answer:
B
Chapter: 9
Q266:
Exhaustively exploring a search tree with branching factor 16 and depth 100 would require computation of the order of ______.
A. 10^100
B. 10^120
C. 10^50
D. 10^10
Correct Answer:
B
Chapter: 9
Q267:
Which search method avoids exploring longer paths by pruning them early?
A. Backtracking
B. Beam Search
C. Branch and Bound
D. Depth First Search
Correct Answer:
C
Chapter: 9
Q268:
Branch and Bound works by cutting off paths that _______.
A. are too deep
B. contain cycles
C. exceed a known best path length
D. lead to leaf nodes
Correct Answer:
C
Chapter: 9
Q269:
What improvement in Branch and Bound uses previous calculations to avoid recomputation?
A. Heuristic estimate
B. Greedy method
C. Dynamic programming
D. Backtracking
Correct Answer:
C
Chapter: 9
Q270:
Which improvement helps Branch and Bound to avoid losing nearby solutions?
A. Overestimate heuristic
B. Underestimate heuristic
C. Random walk
D. Loop detection
Correct Answer:
B
Chapter: 9
Q271:
In dynamic programming, we always prefer the path with _______.
A. more nodes
B. minimum cost
C. highest value
D. longest path
Correct Answer:
B
Chapter: 9
Q272:
What is the A* algorithm?
A. A brute force method
B. A random walk method
C. A combination of Branch and Bound with heuristic and dynamic programming
D. Dynamic cost estimator
Correct Answer:
C
Chapter: 9
Q273:
In A* algorithm, node evaluation is based on ______.
A. depth only
B. heuristic only
C. sum of distance so far and estimated remaining cost
D. random choice
Correct Answer:
C
Chapter: 9
Q274:
A* search is more efficient than simple Branch and Bound due to ______.
A. memory savings
B. faster coding
C. use of underestimates and dynamic programming
D. luck
Correct Answer:
C
Chapter: 9
Q275:
If a node D can be reached with two different paths, which one does A* prefer?
A. The longer one
B. The path with lowest accumulated cost
C. Random one
D. The deepest path
Correct Answer:
B
Chapter: 9
Q276:
Adversarial Search involves how many players or agents?
A. One
B. Two or more
C. None
D. Three or more
Correct Answer:
B
Chapter: 9
Q277:
In Adversarial Search, players generally have ______ goals.
A. same
B. undefined
C. contrary
D. fixed
Correct Answer:
C
Chapter: 9
Q278:
Which of the following games is an example of Adversarial Search?
A. Pac-Man
B. Chess
C. Monopoly
D. Sudoku
Correct Answer:
B
Chapter: 9
Q279:
Player 1 trying to make a line of crosses in tic-tac-toe while Player 2 tries to block them is an example of ______.
A. cooperative behavior
B. branch and bound
C. adversarial goal
D. conflict resolution
Correct Answer:
C
Chapter: 9
Q280:
Adversarial Search is mostly applied in ______.
A. robotics
B. weather prediction
C. board games
D. chatbots
Correct Answer:
C