03-01-Informed-Search.pdf - Informed Search CSE 440 Today I...

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Informed Search CSE 440
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Today I Informed Search Methods I Heuristics I Greedy Search I A * Search
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Example: Pancake Problem
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Search Heuristics I A heuristic is: I A function that estimates how close a state is to a goal
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Search Heuristics I A heuristic is: I A function that estimates how close a state is to a goal I Designed for a particular search problem
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Search Heuristics I A heuristic is: I A function that estimates how close a state is to a goal I Designed for a particular search problem I Examples: Manhattan distance, Euclidean distance for pathing
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Example: Heuristic Function
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Example: Heuristic Function I Heuristic: index of the largest pancake that is still out of place.
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Greedy Search
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Example: Heuristic Function
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Greedy Search: Romania I Expand the node that seems closest ...
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Greedy Search: Romania I Expand the node that seems closest ... Arad
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Greedy Search: Romania I Expand the node that seems closest ... Arad Timisoara Zerind Sibiu
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Greedy Search: Romania I Expand the node that seems closest ... Arad Timisoara Zerind Sibiu Rimnicu Oradea Faragas Arad
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Greedy Search: Romania I Expand the node that seems closest ... Arad Timisoara Zerind Sibiu Rimnicu Oradea Faragas Arad Bucharest Sibiu
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Greedy Search: Romania I Expand the node that seems closest ... Arad Timisoara Zerind Sibiu Rimnicu Oradea Faragas Arad Bucharest Sibiu I What can go wrong?
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Greedy Search I Strategy: expand a node that you think is closest to a goal state I Heuristic: estimate of distance to nearest goal for each state I A common case: I Best-first takes you straight to the (wrong) goal I Worst-case: like a badly-guided DFS
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A * Search Combine UCS and Greedy
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Combining UCS and Greedy S a b c d G e 1 1 1 1 2 8 3 S g=0, h=6 a g=1, h=5 d g=4, h=2 e g=9, h=1 b g=2, h=6 c g=3, h=7 G g=6, h=0 d g=10, h=2 G g=12, h=0
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Combining UCS and Greedy I Uniform-cost orders by path cost, or backward cost g ( n ) .
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  • Winter '15
  • Distance, Romania, Admissible heuristic, Heuristic algorithm

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