1. CS621 : Artificial Intelligence
Pushpak Bhattacharyya CSE Dept., IIT Bombay
Lecture 5 – Other Search Algorithms

2. Iterative Deepening A* : 8-puzzle
H(n) = SUM( Manhattan Distances ) =
= 14 = threshhold 8 2 4 3 1 5 7 6
Start 1 2 3 4 5 6
Goal 7 8

3. Step-1 8 2 8 2 4 4
OL : 3 1 5 3 1 7 6 7 6 5
f = g + h
= = 14
f = g + h
= = 16
Exceeds threshold
CL : empty

4. Step-2 8 2 8 2 4 4
OL : 3 5 3 1 5 7 1 6 7 6
f = g + h
= = 17 > threshold
f = g + h
= = 19
Exceeds threshold 8 2 4 3 1 5
CL : 7 6

5. Revise Threshold
Both Nodes in OL exceed threshold. Therefore, cannot extend search.
Set new threshold to the minimum of f values exceeding threshold.
New threshold = 17
Now conduct search by expanding the nodes on OL.

6. Minimax Search, α- β prnuning
X : 1st player
0 : 2nd player
e(p) = (rows + cols + diagonals open to ‘X’) – (Same to ‘0’)
(1) Start
e(p) = 0 X
X’s Turn X X
e = 8 – 4 = 4
e = 8 – 6 = 2
e = 8 – 5 = 3 X X
0’s Turn
e = 5 – 4 = 1
e = 5 – 3 = 2

7. Minimax X tries to maximize his advantage
At the root layer he tries to maximize 0’s disadvantage (minimize his advantage)
So, minimax tree

8. AND OR Search S if B and C S if A A if D A if E B if E and F C if F
C if G S A B C D E F G

9. AO* AO* has to operate like A* maintaining OL and CL.
For AND connectors ALL the nodes have to be explored.