Virtual Labs

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Aim

Theory

Procedure

Pretest

Demo

Practice

Posttest

References

Contributors

Feedback

Beam Search

Choose difficulty:

Beginner

Intermediate

Advanced

Local beam search with k = 1 is an example of?

a: Markov Decision Process Explanation

Explanation

b: Local Hill Climbing Explanation

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c: Genetic algorithm Explanation

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d: None of the above Explanation

Explanation

What is the primary advantage of local beam search?

a: It can explore multiple paths simultaneously Explanation

Explanation

b: It is always guaranteed to find the optimal solution Explanation

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c: It ensures exhaustive exploration of the search space Explanation

Explanation

d: None of the above Explanation

Explanation

Which of the following statements is true about Local Beam Search? \ Statement 1: Local Beam Search explores a single path at a time. \ Statement 2: Local Beam Search is a memory-intensive search algorithm.

a: only 1 Explanation

Explanation

b: only 2 Explanation

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c: 1 and 2 Explanation

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d: neither 1 and 2 Explanation

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Which of the following best describes local beam search?

a: A search algorithm that expands all possible paths simultaneously Explanation

Explanation

b: A search algorithm that focuses on a single path at a time Explanation

Explanation

c: A search algorithm that selects multiple paths to explore in parallel Explanation

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d: None Explanation

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In beam search, the beam width determines

a: The maximum depth of the search tree Explanation

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b: The probability of selecting a given path for exploration. Explanation

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c: The heuristic evaluation function Explanation

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d: The number of paths selected for exploration at each iteration Explanation

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What is a potential drawback of using a narrow beam width in beam search?

a: Higher computational cost Explanation

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b: Increased memory usage Explanation

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c: Limited exploration of the search space Explanation

Explanation

d: None Explanation

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