MiniMax Search Algorithms: Backward Value Propagation and Optimal Move Selection
This article delves into the intricacies of the MiniMax search algorithm, focusing on the process of expanding the search space and propagating leaf node values backward. It discusses how to select Max and Min values at their respective levels, navigating through a 3-ply search tree. By analyzing nodes with values like 3, 0, 9, and others, we aim to illustrate the steps taken to determine the optimal move for the Max player. Understanding these methodologies enhances strategic decision-making in competitive environments such as games.
MiniMax Search Algorithms: Backward Value Propagation and Optimal Move Selection
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Presentation Transcript
Max Min Max Min Starting node and labels MiniMaxSearch
Max Min Max Min Continue expand the search space
Max Min Max Min Continue expand the search space
Max Min Max Min 2 3 5 9 0 7 4 Expand the search space down 3-ply
Max Min 9 0 3 7 7 Max Min 2 3 5 9 0 7 4 Propagate the leaf values backward Pick Max values at Max Level
Max 3 0 Min 9 0 3 7 7 Max Min 2 3 5 9 0 7 4 Continue propagate the values backward Pick Min values at Min Level
3 Max 3 0 Min 9 0 3 7 7 Max Min 2 3 5 9 0 7 4 Continue propagate the values backward Pick Max values at Max Level
3 Max 3 0 Min 9 0 3 7 7 Max Min 2 3 5 9 0 7 4 The move picked by Max
