Optimization of Enemy's Behavior in Super Mario Bros Game Using Fuzzy Sugeno Model

Abstract

One of the key factors to make the action game more interesting is the smart behavior of an enemy. This paper describes the enhancement of smart enemy's behavior in the game that similar to Super Mario Bros using Sugeno Fuzzy Model. Sugeno Fuzzy Model is applied to regulate the enemy's behavior and determine the steps to be taken. The enhancement of the enemy's behaviors performed in the process of chasing down moving player and enemy's behaviors when meeting the player. Tests on the chasing player process, performed with 4 scenarios and shows achievement of 75% success, while in the game before adding Fuzzy Sugeno Model, the success is only 20%. Meanwhile, testing for enemy's behavior in this game is 100% successful, while in previous games only 33.3%. An enemy behavior logic test is performed to obtain defuzzification results as a Cartesian axis graph. Testing is done using Matlab®. Testing yielded 3 Cartesian axis graphs. Each graph has a behavioral decision. Therefore, there are three enemy's behavior decisions in this game, while Super Mario Bros game only produces 1 graph of Cartesian axis that does not result in enemy's behavior decisions.