ai-lect6 - 1 Last time: search strategies Uninformed: Use...

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Unformatted text preview: 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. 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 3 Depth-first search Node queue: initialization # state depth path cost parent # 1 A-- 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-- 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-- 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-- 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 8 Breadth-first search Node queue: initialization # state depth path cost parent # 1 A-- 9 Breadth-first search Node queue:...
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This note was uploaded on 01/20/2011 for the course CS 6810 taught by Professor Hecker during the Spring '10 term at CSU East Bay.

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ai-lect6 - 1 Last time: search strategies Uninformed: Use...

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