If the shallowest goal node is at some finite depth say d, breadth-first search will eventually find it after expanding all shallower nodes (provided that the branching factor b is finite).[1]
[edit] Optimality ...
The start node is S the goal node is G. A and B are nodes representing intermediate destinations. Each line connecting two nodes represents the path which must be followed to arrive at that new node.
a) Generate and Test Approach: This approach concerns the generation of the state-space from a known starting state (root) of the problem and continues expanding the reasoning space until the goal node or the terminal state is reached.
The top node of the tree is called the Goal node, in that it contains the conclusion. Each tree in the forest has a different Goal node. The leaves of the tree are also referred to as RULE nodes, or one of the types of RULE nodes.
Normally, the loop exits when it finds the goal node. However, at any point before that, it can return a path to the currently best node in OPEN. That node is our best chance of getting to the goal, so it's a reasonable place to go.
Depth-first search always expands one of the nodes at the deepest level of the tree. Only when the search hits a dead end (a nongoal node with no expansion) does the search go back and expand nodes at shallower levels.
Depth-limited search ...
 See also: Search algorithm, Hill climbing, Artificial intelligence, Depth-first search, Goal state
  
|
RSS
