Heuristic Search Methods Quiz
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Questions and Answers

Which type of search techniques systematically evaluate every path in the search space?

  • Heuristic search (correct)
  • Depth-first search
  • Optimal search
  • Breadth-first search
  • What is the main purpose of using a heuristic in search algorithms?

  • To evaluate every path in the search space
  • To generate all child nodes of a parent
  • To reduce the need to explore irrelevant paths (correct)
  • To expand child nodes only if they are better than parent nodes
  • Which hill-climbing algorithm selects the best possible move at each point and requires all child nodes to be generated first?

  • Beam search
  • Simple hill-climbing
  • Steepest-ascent hill-climbing (correct)
  • Depth-first search
  • What does beam search involve in comparison to other hill-climbing algorithms?

    <p>Expansion of two or more nodes in parallel</p> Signup and view all the answers

    Which type of search strategy is used to find the best or shortest route?

    <p>Optimal search</p> Signup and view all the answers

    Study Notes

    Search Techniques

    • Exhaustive search techniques systematically evaluate every path in the search space.

    Heuristics in Search Algorithms

    • The main purpose of using a heuristic is to guide the search towards more promising areas of the search space.

    Hill-Climbing Algorithms

    • Steepest-ascent hill-climbing selects the best possible move at each point and requires all child nodes to be generated first.
    • Beam search involves selecting a fixed number of best nodes (beam width) to expand at each level, unlike other hill-climbing algorithms.

    Search Strategies

    • Optimal search strategies are used to find the best or shortest route.

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    Description

    Test your knowledge of heuristic search methods with this quiz covering depth-first and breadth-first searches, and the use of domain-specific information to reduce search space. Challenge yourself to understand how algorithms can be directed towards solving problems more efficiently.

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