Artificial Intelligence and Soft Computing: Behavioral ... - Arteimi.info

4.3.2 Iterative Deepening A* Algorithm
The iterative deepening search algorithm, discussed earlier, searches the goal
node in a depth first manner at limited depth. In each pass the depth is
increased by one level to test the presence of the goal node in that level. The
A* algorithm, on the other hand, in each pass, selects the least cost (f ) node
for expansion. The iterative deepening A* (or IDA*) algorithm presented
below attempts to combine the partial features of iterative deepening and A*
algorithms together. Here, the heuristic measure is used to check the depth
cut-off, rather than the order of the selection of nodes for expansion. The
algorithm is formally presented below.
Procedure IDA*
Begin
1. Initialize the current depth cut-off c = 1;
2. Push a set of starting nodes into a stack; Initialize the cut-off at
next iteration c’ = ∝;
3. While the stack is not empty do
Begin
Pop stack and get the topmost element n;
If n is the goal, Then report success and
return n with the path from the starting node
Else do
Begin
For each child n’ of n
End;
If f(n’) ≤ c Then push n’ into the stack
Else assign c’ := min (c’, f(n’));
End For;
End While;
4. If the stack is empty and c’ = ∝ Then stop and exit;
5. If the stack is empty and c’≠ ∝ Then assign c:= c’ and return to step 2;
End.