What are the main cons of hill-climbing search?1 pointTerminates at local optimum & Does not find optimum solutionTerminates at global optimum & Does not find optimum solutionDoes not find optimum solution & Fail to find a solutionFail to find a solutionOther:
Question
What are the main cons of hill-climbing search?1 pointTerminates at local optimum & Does not find optimum solutionTerminates at global optimum & Does not find optimum solutionDoes not find optimum solution & Fail to find a solutionFail to find a solutionOther:
Solution
The main cons of hill-climbing search are:
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It often gets stuck at local optima: This means that the algorithm may find a solution that is the best in its immediate vicinity, but not the best overall. This is because hill-climbing search only looks at the immediate neighbors of the current state and chooses the one that improves the situation the most. If it reaches a state where all neighbors are worse, it will stop, even if there are better solutions further away.
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It does not always find the global optimum
Similar Questions
What is the primary objective of the hill climbing algorithm? a. To always select the steepest ascent path in the search space b. To explore all possible paths equally until the goal is found c. To reach the highest point (maximum) in the search space d. To minimize the total cost from the start node to the goal node
Hill Climbing is a heuristic optimization process that iteratively advances towards a better solution at each step in order to find the best solution in a given search space.
________ does more work when each assignment is added to the current partial solution.a)Simple hill Climbingb)Forward searchc)Steepest-Ascent hill-climbingd)Backtrack search
Which search strategy guarntees finding the least-cost solution?Bredth-first searchDepth-first searchUniform-cost search
Explain the advantages of optimal binary search tree.
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