Player modelling is the computational construction of representations of a player’s preferences, skill, behaviour, and emotional state from in-game data. These models enable games to personalise difficulty, content, and recommendations, and to predict future actions. It is a foundational technique for adaptive and AI-driven game systems.
Content
- Techniques span supervised classification of player types, clustering of behavioural traces, and sequence models that predict next actions. Models may be static (player-type taxonomies) or dynamic (online updates during play), and they feed difficulty adjustment, matchmaking, churn prediction, and content recommendation pipelines.