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Table Of Contents
The Applied Artificial Intelligence Workshop
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Suppose there is a game where a heuristic function can evaluate a game state from the perspective of the AI player. For instance, we used a specific evaluation for the tic-tac-toe exercise:
This static evaluation is straightforward to implement on any node. The problem is that as we go deep into the tree of all possible future states, we do not yet know what to do with these scores. This is where the Minmax algorithm comes into play.
Suppose we construct a tree with each possible move that could be performed by each player up to a certain depth. At the bottom of the tree, we evaluate each option. For the sake of simplicity, let's assume that we have a search tree that appears as follows:
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