Virtual Labs

Hill CLimbing is an example of which programming method

a: Greedy Explanation

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b: Dynamic Programming Explanation

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c: Object-oriented programming Explanation

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d: None of them Explanation

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Which of the following is not a variant of hill climbing:

a: Steepest Ascent Explanation

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b: Genetic algorithm Explanation

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c: Random Restart Explanation

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d: Stochastic Explanation

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Which of the following is true regarding Hill Climbing?

a: Hill Climbing may get stuck at local optimas Explanation

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b: Hill climbing does not look ahead beyond the immediate neighbors of the current state Explanation

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c: Hill Climbing is not a complete algorithm Explanation

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d: All of the above Explanation

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The heuristic value of a particular 8 queens configuration is 8. The Steepest Descent Hill Climbing algorithm generates 3 neighbouring states {a: 10, b:6, c:8}. If sideways move is allowed, which state would the algorithm go to next?

a: a Explanation

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b: b Explanation

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c: c Explanation

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d: None of the above, the algorithm terminates Explanation

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In which scenario, Hill Climbing might be a good choice?

a: When the search space is continuous and smooth Explanation

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b: When the objective function is non differentiable Explanation

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c: When the objective function has many peaks and valleys Explanation

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d: When the search space is discrete and has a well defined structure Explanation

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The heuristic value of a particular 8 queens configuration is 10. The Steepest Descent Hill Climbing algorithm generates 3 neighbouring states {a: 10, b:12, c:14}. If sideways move is not allowed, which state would the algorithm go to next?

a: a Explanation

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b: b Explanation

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c: c Explanation

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d: None of the above, the algorithm terminates Explanation

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