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Questions and Answers
What is the primary purpose of informed search methods?
Which statement accurately describes a heuristic in the context of search algorithms?
What is a significant drawback of the hill-climbing algorithm?
In Best-First search, how is the OPEN list utilized?
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What differentiates heuristic search from blind search techniques?
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What does a hill-climbing algorithm do when it encounters a peak during its search?
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Which characteristic is NOT associated with Best-First search?
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Which of the following best describes the function of heuristics during the search process?
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What role does randomness play in solving the limitations of hill-climbing search?
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Study Notes
Introduction
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Artificial Intelligence (AI) often utilizes heuristics to guide searches and make them more efficient.
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These heuristics help improve average search performance.
Heuristic Search
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Heuristic search involves utilizing domain-specific knowledge to traverse the search space.
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Instead of brute-force "blind" methods, it employs knowledge to guide the search.
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A heuristic is essentially a rule of thumb that can assist in solving a problem, often by trial and error.
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The heuristic function focuses on problem-specific knowledge to guide the search.
Hill-Climbing Search
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Hill-climbing algorithms, also known as steepest ascent algorithms, continuously move in the direction of improving values (uphill).
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They terminate when they reach a peak where no neighboring node has a higher value.
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Local Maxima: Hill-climbing can get trapped in local maxima, which are peaks that are not the highest point within the search space.
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Adding randomness to the search can help overcome this issue and avoid getting stuck.
Best-First Search
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Best-First Search prioritizes exploring nodes based on their heuristic evaluation function.
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Untested nodes are held within the OPEN list, while evaluated nodes are stored in the CLOSED list.
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The OPEN list functions as a priority queue, enabling nodes to be dequeued in order of their evaluation function value.
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Description
This quiz explores important concepts in Artificial Intelligence, focusing on heuristic search and hill-climbing algorithms. Understand how heuristics can optimize search processes and the challenges posed by local maxima. Test your knowledge on key principles and applications of these search strategies.
