ai-lect6 - Last time search strategies Uninformed Use only...

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1 Last time: search strategies Uninformed:  Use only information available in the problem formulation Breadth-first Uniform-cost Depth-first Depth-limited Iterative deepening Informed:  Use heuristics to guide the search Best first: Greedy search –  queue first nodes that maximize heuristic “desirability” based on  estimated path cost from current node to goal; A* search –  queue first nodes that maximize sum of path cost so far and estimated  path cost to goal. Iterative improvement –  keep no memory of path; work on a single current state and  iteratively improve its “value.” Hill climbing –  select as new current state the successor state which maximizes  value. Simulated annealing –  refinement on hill climbing by which “bad moves” are  permitted, but with decreasing size and frequency. Will find global extremum.
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2 Exercise: Search Algorithms The following figure shows a portion of a partially expanded search tree.   Each arc between nodes is labeled with the cost of the corresponding  operator, and the leaves are labeled with the value of the heuristic function,  h . Which node (use the node’s letter) will be expanded  next by each of the  following search algorithms? (a) Depth-first search (b) Breadth-first search (c) Uniform-cost search (d) Greedy search (e) A* search   5 D 5 A C 5 4 19 6 3 h=15 B F G E h=8 h=12 h=10 h=10 h=18 H h=20 h=14
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3 Depth-first search Node queue: initialization # state depth path cost parent # 1 A 0 0 --
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4 Depth-first search Node queue: add successors to queue front; empty queue from top # state depth path cost parent # 2 B 1 3 1 3 C 1 19 1 4 D 1 5 1 1 A 0 0 --
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5 Depth-first search Node queue: add successors to queue front; empty queue from top # state depth path cost parent # 5 E 2 7 2 6 F 2 8 2 7 G 2 8 2 8 H 2 9 2 2 B 1 3 1 3 C 1 19 1 4 D 1 5 1 1 A 0 0 --
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6 Depth-first search Node queue: add successors to queue front; empty queue from top # state depth path cost parent # 5 E 2 7 2 6 F 2 8 2 7 G 2 8 2 8 H 2 9 2 2 B 1 3 1 3 C 1 19 1 4 D 1 5 1 1 A 0 0 --
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7 Exercise: Search Algorithms The following figure shows a portion of a partially expanded search tree.   Each arc between nodes is labeled with the cost of the corresponding  operator, and the leaves are labeled with the value of the heuristic function,  h . Which node (use the node’s letter) will be expanded  next by each of the  following search algorithms? (a) Depth-first search (b) Breadth-first search (c) Uniform-cost search (d) Greedy search (e) A* search   5 D 5 A C 5 4 19 6 3 h=15 B F G E h=8 h=12 h=10 h=10 h=18 H h=20 h=14
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8 Breadth-first search Node queue: initialization # state depth path cost parent # 1 A 0 0 --
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9 Breadth-first search Node queue: add successors to queue end; empty queue from top # state depth path cost parent # 1 A 0 0 -- 2 B 1 3 1 3 C 1 19 1 4 D 1 5 1
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