Perancangan dan Pembuatan Action Game dengan Artificial Intelligence dan Machine Learning

Samuel Vincentius Lidianto, Gregorius Satia Budhi, Rolly Intan


Playing games is a way for someone to relieve their stress. However, based on reality, most people are easily to get bored after playing several rounds of game. To overcome this problem, this thesis will create a game where the enemy can give fast respons when fighting the player and may develop the AI’s capabilities.

The genre of this game is action. The AI in this game will use two methods: fuzzy state machine and machine learning. Fuzzy state machine is a method to choose the best response towards the enemy. Machine learning is used to update the active file rules of the enemy.

The result from this experiment stated that action game with fuzzy state machine and machine learning can make the enemy to give better respons after being played by the player.


Fuzzy State Machine, Fuzzy Rules, Game Based Learning, Action Game

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