GAImE : Investigating game AI for enhanced user experience

Abstract

Over the last few decades, the business of digital and video games has risen exponentially. Aside from the higher fidelity of the graphics and the more involving game plots and narratives, GameAI is an area which is gaining more popularity in the game development industry. Research and development in the area is registering increased progress in a number of AI technologies. Game AI research that has been ongoing for the past two decades has also seen an increase into the investigation of how AI can be used to enhance the user’s game play experience rather than just learning how to beat human players. The concept in applying AI techniques is to make NPCs (Non-Player Characters) appear intelligent by making use of different techniques. NPCs are AI-controlled characters within the video game which can have different typologies such as companions and enemies. This thesis investigates different AI techniques for the generation of NPCs and how these may in turn affect the user’s experience by evaluating user engagement and satisfaction. Game studies indicate that making use of eye-catching graphics, great sound effects and music, are essential game elements and may improve user satisfaction. However, in this thesis, we propose an additional element that may add to the user satisfaction in game play – intelligence in NPCs. As a proof of concept, a survival game is developed using Unity 3D. Different AI techniques, such as FSM, Behaviour Based NPCs and RL Agents have been adopted and adapted to the game’s NPCs and these have been in turn tested and evaluated from the user experience perspective. Whilst for behaviour-based NPC’s the actions were predefined, RL agents learned actions depending on the in-game rewards obtained. The satisfaction of the user is calculated by using the Game User Experience Satisfaction Scale. This gives a good indication of the parts of the game which make the user feels more satisfied. The results record a total average satisfaction of 5.8/7 on the GUESS scale. The survey results also indicated that users preferred the behaviour-based approach in favour of RL. This could be due that for these particular group of users preferred to predict and anticipate the actions and reactions of the behaviour-based companion NPC since all of its actions were predefined. These preferences are subjective depending on the type of audience playing the game.