treeSearching-sp10

# treeSearching-sp10 - Tree Searches Source David Lee...

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Tree Searches Source: David Lee Matuszek

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2 Tree searches A tree search starts at the root and explores nodes from there, looking for a goal node (a node that satisfies certain conditions, depending on the problem) For some problems, any goal node is acceptable ( N or J ); for other problems, you want a minimum-depth goal node, that is, a goal node nearest the root (only J ) L M N O P G Q H J I K F E D B C A Goal nodes
3 Depth-first searching A depth-first search ( DFS ) explores a path all the way to a leaf before backtracking and exploring another path For example, after searching A , then B , then D , the search backtracks and tries another path from B Node are explored in the order A B D E H L M N I O P C F  G J K Q N will be found before J L M N O P G Q H J I K F E D B C A

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4 How to do depth-first searching Put the root node on a stack; while (stack is not empty) {     remove a node from the stack;     if (node is a goal node) return success;     put all children of node onto the stack; } return failure; At each step, the stack contains some nodes from each of a number of levels The size of stack that is required depends on the branching factor b While searching level n , the stack contains approximately ( b-1)*n nodes When this method succeeds, it doesn’t give the path
5 Recursive depth-first search search(node):      if node is a goal,  return success;      for each child c of node {           if search(c) is successful,  return success;      }      return failure; The (implicit) stack contains only the nodes on a path from the root to a goal The stack only needs to be large enough to hold the deepest search path When a solution is found, the path is on the (implicit) stack, and can be extracted as the recursion “unwinds” print node and print c and

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treeSearching-sp10 - Tree Searches Source David Lee...

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