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given depth without finding a solution Evaluation of IDS
n༆ Evaluation of IDS Completeness:
YES n༆ Time complexity: O(bd) n༆ Completeness:
q༇ YES
Time complexity: O(bd) n༆ Space complexity: O(bd) q༇ n༆ q༇ Same as DFS 11 9/20/13 Evaluation of IDS
n༆ Completeness:
YES
Time complexity: O(bd)
Space complexity: O(bd) Iterative Deepening Search
n༆ q༇ n༆
n༆ q༇ n༆ Same as DFS Optimality:
q༇ YES if step cost is 1. Bidirectional Search n༆ Two simultaneous searches from start and goal.
Motivation: bd/2 + bd/2 much less than bd
Before a node is expanded it is checked if it is in the fringe of the other
search (can be done in constant time using a hash table).
Need to keep at least one of the search trees in memory
Time complexity: O(bd/2).
Space complexity: same.
Complete and optimal (for uniform step costs) if both searches are BFS
q༇ n༆ n༆
n༆
n༆
n༆ n༆ Analogous to BFS: explores a complete layer
of nodes before proceeding to the next one.
Combines benefits of DFS and BFS. Bidirectional Search Issues in applying:
n༆ The predecessor of each node should be efficiently computable.
q༇ n༆ n༆ When actions are easily reversible. Goal node: sometimes not unique or known explicitly (e.g., in
chess).
Memory consumption 12 9/20/13 Comparison of search strategies
Criterion BreadthFirst Uniformcost DepthFirst Depthlimited Iterative
deepening Bidirection
al search Complete? YES* YES* NO YES, if l ≥ d YES YES* Time bd+1 bC*/e bm bl bd bd/2 Space bd+1 bC*/e bm bl bd bd/2 Optimal? YES* YES* NO NO YES YES 13...
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This note was uploaded on 02/10/2014 for the course CS 440 taught by Professor Staff during the Fall '08 term at Colorado State.
 Fall '08
 Staff
 Artificial Intelligence

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