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QUESTION 1 In depth - first search, which data structure is typically used for storing the frontier? A . Queue B . Stack C .
QUESTION
In depthfirst search, which data structure is typically used for storing the frontier?
A
Queue
B
Stack
C
Priority Queue
D
Heap
points
QUESTION
In breadthfirst search, how are nodes expanded from the frontier?
A
Nodes are expanded based on their depth in the search tree.
B
Nodes are expanded based on their heuristic values.
C
Nodes are expanded in a random order.
D
Nodes are expanded in the order they were added to the frontier.
points
QUESTION
What is the primary characteristic of Local Search algorithms?
A
They guarantee to find the optimal solution.
B
They systematically explore the entire search space.
C
They focus on improving the current solution iteratively.
D
They always expand nodes based on heuristic values.
points
QUESTION
Which of the following statements about breadthfirst search BFS is true?
A
BFS is always faster than depthfirst search.
B
BFS guarantees the shortest path to the goal.
C
BFS requires less memory compared to depthfirst search.
D
BFS is not suitable for infinite state spaces.
points
QUESTION
In Genetic Algorithms, what does the term "mutation" refer to
A
The process of selecting individuals for reproduction.
B
The process of generating new individuals by combining genetic material from parents.
C
The process of randomly altering the genetic material of individuals.
D
The process of evaluating the fitness of individuals in the population.
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QUESTION
Which of the following best describes the A algorithm's memory usage compared to other search algorithms?
A
A uses more memory than uninformed search algorithms.
B
A uses less memory than uninformed search algorithms.
C
A uses the same amount of memory as uninformed search algorithms.
D
A memory usage depends on the heuristic function used.
points
QUESTION
What heuristic function is commonly used with the Greedy algorithm?
A
Admissible heuristic
B
Inadmissible heuristic
C
Null heuristic
D
Consistent heuristic
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QUESTION
Which characteristic distinguishes Simulated Annealing from other Local Search algorithms?
A
It always moves to a neighboring state with a higher value.
B
It uses temperature parameter to control the probability of accepting worse solutions.
C
It explores the entire search space exhaustively.
D
It guarantees to find the global optimum.
points
QUESTION
What is the role of the heuristic function in A search?
A
It provides an estimate of the cost from the start node to the current node.
B
It determines the order in which nodes are expanded.
C
It calculates the exact distance between nodes.
D
It prevents the algorithm from exploring certain paths.
points
QUESTION
What distinguishes Local Beam Search from other Local Search algorithms?
A
It maintains multiple states and selects the best ones to continue the search.
B
It always moves to the neighboring state with the highest value.
C
It uses a populationbased approach to explore the search space.
D
It systematically explores the entire search space.
points
QUESTION
Which heuristic is considered admissible in A search?
A
One that underestimates the cost to reach the goal.
B
One that overestimates the cost to reach the goal.
C
One that provides an exact cost to reach the goal.
D
One that is unrelated to the cost to reach the goal.
points
QUESTION
What is the primary characteristic of an uninformed search algorithm?
A
It explores the search space without considering the problem domain.
B
It utilizes domainspecific knowledge.
C
It prioritizes the expansion of nodes based on heuristic values.
D
It always guarantees the optimal solution.
points
QUESTION
Which uninformed search algorithm combines the advantages of both depthfirst and breadthfirst search?
A
UniformCost Search
B
Bidirectional Search
C
Iterative Deepening Search
D
Greedy BestFirst Search
points
QUESTION
Which statement accurately describes the A algorithm?
A
It is guaranteed to find the optimal solution.
B
It expands nodes in a depthfirst manner.
C
It is admissible but not consistent.
D
It is not suitable for problems with large search spaces.
points
QUESTION
In Hill Climbing, what happens if no neighboring state has a higher value than the current state?
A
The algorithm terminates.
B
The algorithm moves to a random neighboring state.
C
The algorithm moves to the highestvalued neighboring state found so far.
D
The algorithm returns the
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