Beyond Metrics: A Human Validation Study of Procedural Personas in a Continuous Game Arena

This dataset accompanies the paper “Beyond Metrics: A Human Validation Study of Procedural Personas in a Continuous Game Arena” (submitted for double‑blind review). It contains the gameplay videos used as stimuli in the user study, the training plots for the five reinforcement‑learning personas, the raw survey data, and the complete statistical analysis output. All materials are provided to facilitate reproducibility of the reported results. File overview baseline.mp4, runner.mp4, survivalist.mp4, monster-killer.mp4, treasure-collector.mp4 – The five 30‑second gameplay clips shown to participants in the within‑subjects forced‑choice identification and believability study. Each video features one of the five procedural persona agents (Baseline, Runner, Survivalist, Monster Killer, Treasure Collector) acting in the evaluation arena described in the paper. The clips are exactly the stimuli presented under Greek‑letter labels (Alpha–Omega). training-plots.7z – Compressed archive containing per‑persona TensorBoard training plots (cumulative reward, episode length, policy entropy, extrinsic reward, extrinsic value estimate, policy loss, and value loss) for all five personas over 1 million training steps. raw_data.xlsx – The fully anonymized raw survey responses (exported from Google Forms), including demographics, forced‑choice identification answers, believability ratings, and consistency ratings for the 34 participants retained after attention‑check exclusion. analysis_report.txt – Human‑readable output of the Python analysis pipeline that reproduces all descriptive statistics, confusion matrices, and exploratory correlations reported in the paper. All personal information has been removed from the survey data; the videos and plots contain no identifying metadata. The training code, Unity project, and configuration files are available in the companion GitHub repository (link currently omitted for double‑blind review).