Artificial Intelligence in FPS Games: NPC Difficulty Effects on Gameplay




Journal Title

Journal ISSN


Volume Title


Springer, Cham


Book chapter

Peer reviewed



This report explores the use of fuzzy logic within computer games, with specific respect to their use of Artificial Intelligence (AI) within the games’ enemy Non-Player Characters (NPCs), in order to affect the game’s overall difficulty. The way in which AI is affected varies across different games; games within the same genre often share multiple statistics and values, and these can be applied to an NPC in order to make the game easier or harder. Games within the First-Person Shooter (FPS) genre, for example, can always affect their difficulty by changing an enemy character’s accuracy with weapons or overall damage output as these would all change how likely they are to defeat the player in a combat scenario. In this document, we will be detailing the development and structure of the multiple input Mamdani styled fuzzy inference system (FIS) that we developed in order to rate a given NPC’s difficulty based on the rankings they have been given for these shared statistics.



Artificial intelligence, Non-player characters, First-person shooter, Mamdani, Fuzzy controller


Hubble A., Moorin J., Khuman A.S. (2021) Artificial Intelligence in FPS Games: NPC Difficulty Effects on Gameplay. In: Carter J., Chiclana F., Khuman A.S., Chen T. (eds) Fuzzy Logic: Recent Applications and Developments. Springer, Cham, pp. 165-190


Research Institute

Institute of Artificial Intelligence (IAI)