Jackson Fuller Part of CW18
Since Bartle’s taxonomy of player types, various researchers have attempted to identify and categorise player behaviours. However, player types have proven to be inefficient which has paved the way for trait models instead. Research into player traits is fairly recent and so far, has only been used in subjective questionnaires. This can lead to a lack of understanding of how players make certain decisions in game scenarios.
This project attempts to address this problem by creating a framework that defines various behaviours that players exhibit in relation to their player traits. An artificial agent will be created to display these behaviours in a video game setting to provide an understanding of how a player’s trait orientation can inform their actions in each scenario. The scenarios created for the agent to interact in will be informed by the subjective survey questions designed to identify player traits.
It is expected that the knowledge from this project can be used to predict player behaviours based on the scenarios that developers have created. This leaves the potential to personalise a game for multiple player traits or cater towards a specific one.