An Empirical Evaluation of Evaluation Metrics of Procedurally Generated Mario Levels
Julián P. Mariño, Willian Reis, Levi H. S. Lelis · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · 2015
There are several approaches in the literature for automatically generating Infinite Mario Bros levels. The evaluation of such approaches is often performed solely with computational metrics such as leniency and linearity. While these metrics are important for an initial exploratory evaluation of the content generated, it is not clear whether they are able to capture the player's perception of the content generated. In this paper we evaluate several of the commonly used computational metrics. Namely, we perform a systematic user study with procedural content generation systems and compare the insights gained from our user study with those gained from analyzing the computational metric values. The results of our experiment suggest that current computational metrics should not be used in lieu of user studies for evaluating content generated by computer programs.