MCQs

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Overall MCQs for Reference

What is the first step in the AI problem-solving process?
a. Develop an algorithm
b. Define the problem
c. Test the solution
d. Implement the solution
Answer: b. Define the problemplacementpreparation
Which strategy is commonly used in uninformed search?
a. Hill climbing
b. Greedy best-first search
c. Breadth-first search
d. Genetic algorithm
Answer: c. Breadth-first searchsanfoundry
What is the main task of a problem-solving agent in AI?
a. Solve the given problem and reach the goal
b. To find out which sequence of actions will get to the goal state
c. All of the mentioned
d. None of the above
Answer: c. All of the mentionedsanfoundry
Which search technique explores the deepest unexplored nodes first?
a. Breadth-first search
b. Depth-first search
c. Best-first search
d. Uniform-cost search
Answer: b. Depth-first searchsiteforinfotech
What is the role of heuristic in AI problem-solving?
a. Guaranteed solution
b. Shortcut for good solution
c. Random decision
d. Exact algorithm
Answer: b. Shortcut for good solutionplacementpreparation
Which algorithm is widely used for pathfinding in AI?
a. Merge sort
b. A* algorithm
c. Quick sort
d. Brute force
Answer: b. A* algorithmjavaguides
Which method divides problems into smaller sub-problems?
a. Depth-first search
b. Divide and conquer
c. Hill climbing
d. Backtracking
Answer: b. Divide and conquerplacementpreparation
Which AI problem-solving method involves “trial and error”?
a. Hill climbing
b. Genetic algorithm
c. Brute force
d. Beam search
Answer: a. Hill climbingjavaguides
In AI, what does state-space search mean?
a. Searching for states in different spaces
b. Representation of all possible states of a system
c. Search between two databases
d. None of the above
Answer: b. Representation of all possible states of a systemgtu-mcq
Which technique is designed to optimize solutions by simulating cooling processes?
a. Depth-first search
b. Breadth-first search
c. Simulated annealing
d. Greedy search
Answer: c. Simulated annealingjavaguides
What is the main use of adversarial search in AI problem-solving?
a. Recommendation engines
b. Game playing
c. Summarization
d. Clustering
Answer: b. Game playingsanfoundry
Which search strategy is also known as “uninformed search”?
a. Breadth-first search
b. Heuristic search
c. Genetic search
d. Hill climbing
Answer: a. Breadth-first searchsiteforinfotech+1
What is an admissible heuristic?
a. Overestimates cost to goal
b. Underestimates cost to goal
c. Never overestimates cost to goal
d. Random solution
Answer: c. Never overestimates cost to goaljavaguides
Which search approach is used when path cost is the priority?
a. Uniform-cost search
b. Depth-first search
c. Greedy search
d. Hill climbing
Answer: a. Uniform-cost searchjavaguides
Branch and bound is used in AI for:
a. Storing data efficiently
b. Solving optimization problems
c. Data mining
d. Feature selection
Answer: b. Solving optimization problemsjavaguides
The concept of “backtracking” in AI involves:
a. Abandoning a solution entirely
b. Returning to previous states and trying alternatives
c. Jumping to the best guess
d. Using brute force
Answer: b. Returning to previous states and trying alternativesjavaguides
Which technique is most suitable for solving assignment problems?
a. Greedy search
b. Hungarian algorithm
c. Hill climbing
d. Simulated annealing
Answer: b. Hungarian algorithmjavaguides
What is the main aim of the alpha-beta pruning algorithm?
a. Increase search depth
b. Prune suboptimal branches in game tree search
c. Solve optimization problems
d. Enhance neural networks
Answer: b. Prune suboptimal branches in game tree searchslideshare
Which AI technique is used for decision analysis under uncertainty?
a. Bayesian networks
b. Depth-first search
c. Backtracking
d. Adversarial search
Answer: a. Bayesian networkssanfoundry
What is hill climbing similar to?
a. Local search optimization
b. Tree traversal
c. Statistical inference
d. Logical reasoning
Answer: a. Local search optimizationjavaguides
Which of the following does not guarantee to find a solution and may require backtracking?
a. Depth-first search technique
b. Breadth-first search technique
c. Iterative deepening search technique
d. Heuristic search technique
Answer: a. Depth-first search techniquesiteforinfotech
The Bellman-Ford algorithm in AI is primarily used for:
a. Classification problems
b. Finding shortest paths in graphs with negative weights
c. Data mining
d. Clustering
Answer: b. Finding shortest paths in graphs with negative weightsjavaguides
Which technique is suitable for CSPs (Constraint Satisfaction Problems)?
a. Hill climbing
b. Backtracking
c. Brute force
d. Genetic algorithm
Answer: b. Backtrackingsanfoundry
What is dynamic programming used for in AI?
a. Randomizing results
b. Breaking down problems into simpler subproblems
c. Enhancing neural networks
d. Mapping state-space
Answer: b. Breaking down problems into simpler subproblemsjavaguides
Which search algorithm is complete and optimal for small branching factor and depth?
a. Depth-first search
b. Breadth-first search
c. Hill climbing
d. Simulated annealing
Answer: b. Breadth-first searchsanfoundry+1
What is the purpose of the minimax algorithm?
a. Evaluate game positions and choose optimal moves
b. Enhance memory usage
c. Summarize data
d. Random selection
Answer: a. Evaluate game positions and choose optimal movesslideshare
Which algorithm would you use to solve a maze problem in Python?
a. Binary search
b. Depth-first search
c. Linear search
d. Bubble sort
Answer: b. Depth-first searchplacementpreparation
Which term is used for judgmental or “commonsense” part of problem solving?
a. Heuristic
b. Critical
c. Analytical
d. Value based
Answer: a. Heuristicbbsbec
Which AI search strategy is based on evaluating nodes using a cost function f(n) = g(n) + h(n)?
a. Greedy best-first search
b. A* algorithm
c. Uniform-cost search
d. Hill climbing
Answer: b. A* algorithmjavaguides
Which search technique avoids exploring infinitely deep paths?
a. Depth-first search
b. Depth-limited search
c. Breadth-first search
d. Local search
Answer: b. Depth-limited searchjavaguides
Which AI method efficiently finds solutions by combining features of uniform-cost and greedy searches?
a. A* algorithm
b. Genetic algorithm
c. Minimax
d. Alpha-beta pruning
Answer: a. A* algorithmjavaguides
What is the main benefit of using heuristic searches in AI?
a. Guaranteed optimality
b. Faster path to a satisfactory solution
c. Increased memory
d. Random selection
Answer: b. Faster path to a satisfactory solutionplacementpreparation+1
Which algorithm is ideal for solving travelling salesman problems in AI?
a. Depth-first search
b. Simulated annealing
c. Breadth-first search
d. Hill climbing
Answer: b. Simulated annealingjavaguides
Which problem-solving agent makes decisions based on percept history and current perception?
a. Simple reflex agent
b. Model-based agent
c. Utility-based agent
d. Learning agent
Answer: b. Model-based agentsanfoundry
What is “local search” in AI?
a. Search that considers all global possibilities
b. Search that operates on current state and moves to neighbors
c. Search that restarts entirely
d. Search by brute force
Answer: b. Search that operates on current state and moves to neighborsjavaguides
What is used for solving optimization problems in AI by considering only local changes?
a. Brute force
b. Hill climbing
c. Breadth-first search
d. Genetic algorithm
Answer: b. Hill climbingjavaguides
The “greedy best-first search” algorithm prioritizes nodes based on:
a. Lowest f(n)
b. Highest heuristic value
c. Closest to solution based on heuristic
d. Largest g(n)
Answer: c. Closest to solution based on heuristicjavaguides
Which approach is best for multi-agent planning in problem-solving?
a. Classical planning
b. Distributed planning
c. Local search
d. Random traversal
Answer: b. Distributed planningsanfoundry
What is the output of applying alpha-beta pruning in adversarial search?
a. Increased search space
b. Reduced search space
c. Enhanced cost calculation
d. More random decisions
Answer: b. Reduced search spaceslideshare
Which method is frequently used for reasoning in uncertain environments?
a. Constraint satisfaction
b. Bayesian inference
c. Brute force
d. Simulated annealing
Answer: b. Bayesian inferencesanfoundry
What is the “branching factor” in search algorithms?
a. Number of children per node
b. Number of leaf nodes
c. Minimum depth level
d. Path cost
Answer: a. Number of children per nodeinterviewbit
Which technique is most useful for large state-space problems?
a. Brute force
b. Heuristic search
c. Backtracking
d. Depth-limited search
Answer: b. Heuristic searchplacementpreparation+1
Which algorithm is designed for shortest path finding with potentially negative edge weights?
a. Bellman-Ford
b. A* algorithm
c. Dijkstra’s algorithm
d. Greedy best-first search
Answer: a. Bellman-Fordjavaguides
CSP (Constraint Satisfaction Problem) can be efficiently solved using:
a. Backtracking
b. Random walk
c. Breadth-first search
d. Depth-first search
Answer: a. Backtrackingsanfoundry+1
The main goal of an AI problem-solving agent is to:
a. Maximize computational cost
b. Reach a goal state efficiently
c. Randomly select solutions
d. Create more states
Answer: b. Reach a goal state efficientlysanfoundry
In problem-solving, which search algorithm typically uses a queue data structure?
a. Breadth-first search
b. Hill climbing
c. Depth-first search
d. Simulated annealing
Answer: a. Breadth-first searchsanfoundry
What is “state space” in AI?
a. Physical space representation
b. Set of all possible configurations/states of a problem
c. Only goal state representation
d. None of the above
Answer: b. Set of all possible configurations/states of a problemgtu-mcq
Which algorithm is used for assignment problems in optimization?
a. Greedy search
b. Hungarian algorithm
c. Simulated annealing
d. Brute force
Answer: b. Hungarian algorithmjavaguides
What is a production system in AI problem-solving?
a. System that produces goods
b. Set of rules and actions for reaching goals
c. Only used in neural networks
d. Random selection of rules
Answer: b. Set of rules and actions for reaching goalssiteforinfotech
Which algorithm allows exploring all possible permutations efficiently in Python?
a. itertools.combinations
b. itertools.permutations
c. numpy.sort
d. pandas.DataFrame
Answer: b. itertools.permutationsplacementpreparation

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