<![CDATA[In computer fighting games , the ability of players to play with Non-Player Characters (NPC) is essential. A poorly designed NPC causes poor player engagement due to predictable behaviour, thus leads to unsatisfactory playing experience. We propose utility-based AI selected by genetic algorithm to determine the utility functions of each NPC action. We applied ELO ratings (usually used in chess game) to determine fitness function. Utility-based artificial intelligence can deliver human-like NPC with varied decision-making and can employ many forms of function to calculate the AI utility value. Tests on chromosomes in each generation were also carried out to obtain different responses. The Pearson Correlation coefficient is used to obtain an analysis of the influence of each assessment variable. The simulation results verify the validity of our analysis and show that our scheme influences the satisfaction level of game users]]>
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