Basic Search Problem

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Basic Search Problem
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Search Tree from Net
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Depth-First Search
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Breadth-First Search
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Heuristically Informed Methods
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Hill Climbing
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Problems withHill Climbing
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Beam Search (1)
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Beam Search (2)
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Beam Search (3)
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Beam Search (4)
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Optimal Search
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Branch and Bound (1)
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Branch and Bound (2)
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Branch and Bound (3)
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Branch and Bound (4)
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Branch and Bound (5)
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Branch and Bound (6)
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Branch and Bound (7)
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Branch and Bound (8)
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Branch and Bound (9)
Dead end
Goal
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Branch and Bound (10)
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Branch and Bound (11)
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BB with Underestimates (1)
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BB with Underestimates (2)
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BB with Underestimates (3)
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BB with Underestimates (4)
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Dynamic Programming
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BB with Dynamic Programming (1)
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BB with Dynamic Programming (2)
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BB with Dynamic Programming (3)
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BB with Dynamic Programming (4)
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BB with Dynamic Programming (5)
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BB with Dynamic Programming (6)
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A Algorithm

• Form a one-element queue consisting of a
  zero-length path that contains only the root
  node.
• Until the first path in the queue terminates at
  the goal node or the queue is empty,
• Remove the first path from the queue create new
  paths by extending the first path to al the
  neighbors of the terminal node.
• Reject all paths with loops.
• If two or more paths reach a common node, delete
  all those paths except the one that reaches the
  common node with the minimum cost.
• Sort the entire queue by the sum of the path
  length and a lower-bound estimate of the cost
  remaining, with least-cost paths in front.
• If the goal node is found, announce success
  otherwise, announce failure.

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Obstacle-Avoidance Problem
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Configuration-Space Transformation
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New Configuration Space
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Visibility Graph
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Solution by Shortest Paths