This document discusses game playing algorithms. It introduces the Min Max algorithm and Alpha Beta pruning algorithm. It provides an example of calculating the best decision for a game using the Min Max algorithm, which results in a board value of 214. It then shows an example of applying Alpha Beta pruning to the same game, which results in a lower board value of 174 by pruning branches that do not need to be evaluated.

1. Game Playing -Example
Dr. J. Annrose
SXCCE

2. Game Playing
5 7 10 3 1 2 9 9 8 2 9 3

3. Game Playing Algorithms
Min Max Algorithm
Alpha Beta Pruning

4. Min Max Algorithm
5 7 10 3 1 2 9 9 8 2 9 3
bd = 214
Max
Min
Max 7 10 2 9 8 9
7 2 8
8

5. Alpha Beta Pruning
5 7 10 3 1 2 9 9 8 2 9 3
𝞪 = - ∞
𝞫 = ∞
Initialization
𝞪 = - ∞
𝞫 = ∞
Pruning
Condition
𝞪 >= 𝞫
𝞪 = - ∞
𝞫 = ∞
𝞪 = - ∞
𝞫 = ∞
Max
Min
Max
5
7
𝞪 = - ∞
𝞫 = 7
7
7
10
10
7
𝞪 = 7
𝞫 = ∞
𝞪 = 7
𝞫 = ∞
7
7
𝞪 = 7
𝞫 = ∞
𝞪 = 7
𝞫 = ∞
8
8
8
𝞪 = 7
𝞫 = 8
9
9
8
8
8
bd = 174
7