Many researchers have addressed the use of search algorithms
in artificial intelligence, and studies have focused on
improving the efficiency of artificial intelligence in analyzing
in game analytics.This will contribute to
improving the design of more intelligent and interactive artificial
intelligence systems within games.Wang et al. (2021) noted that incorporating algorithms such as A*
and Minimax contributed to improving AI's ability to analyze
complex environments and predict player behavior.Hence, the
idea of this research was to fill this gap by analyzing and evaluating how search algorithms are applied to several game models, and
comparing their effectiveness in terms of speed, accuracy, and
adaptability to changing environments."The name "minimax" comes from minimizing
the loss involved when the opponent selects the strategy that gives
maximum loss and is useful in analyzing the first player's decisions
both when the players move sequentially and when the players move
simultaneously".Recent studies show growing interest in using search algorithms to
improve AI performance in digital games, particularly games that rely
on multiple decision-making, such as chess and role-playing games.