Persona Agents from Playtraces and Emotion

Abstract

This paper proposes a novel pipeline for generating agents that simulate player behaviour. By clustering player traces and using evolutionary algorithms to evolve parametric agents to best represent those clusters, our pipeline creates persona agents that represent the behavioural space of players. We here propose clustering playtraces based on behaviour, emotional experience and a mixture of both. We implement the pipeline on a test bed game and using 182 collected player traces with both behavioural and emotional information, we demonstrate that our persona agents can generate diverse player-like behaviour both in the level used to evolve them but also in a previously unseen level. We further find that using emotional information leads to better behavioural coverage on both levels. Although on its early stages, our approach offers a new perspective on how game developers and testers can gather insights on player behaviour without having to rely on extensive user testing.