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Depth-First Search (DFS) Properties. Non-optimal solution path Incomplete unless there is a depth bound Exponential time Linear space. BFS. Comments on Iterative Deepening Search. Complexity Space complexity = O( bd ) Time Complexity - PowerPoint PPT Presentation
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Depth-First Search (DFS) Properties
• Non-optimal solution path• Incomplete unless there is a depth bound• Exponential time• Linear space
BFS
Comments on Iterative Deepening Search
• Complexity– Space complexity = O(bd)– Time Complexity
• = O(bd) (i.e., asymptotically the same as BFS or DFS in the the worst case)
• The overhead in repeated searching of the same subtrees is small relative to the overall time– e.g., for b=10, only takes about 11% more time than DFS
• A useful practical method– combines
• guarantee of finding an optimal solution if one exists (as in BFS)• space efficiency, O(bd) of DFS• But still has problems with loops like DFS
12
Time requirements for depth-first iterative deepening on binary tree
Nodes at each level
1
2
4
8
16
32
64
128
Nodes searched by DFS
1
+2 = 3
+4 = 7
+8 = 15
+16 = 31
+32 = 63
+64 = 127
+128 = 255
Nodes searched by iterative DFS
1
+3 = 4
+7 = 11
+15 = 26
+31 = 57
+63 = 120
+127 = 247
+255 = 502
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