  Achieving optimal balance in games is essential to their success, yet reliant
on extensive manual work and playtesting. To facilitate this process, the
Procedural Content Generation via Reinforcement Learning (PCGRL) framework has
recently been effectively used to improve the balance of existing game levels.
This approach, however, only assesses balance heuristically, neglecting actual
human perception. For this reason, this work presents a survey to empirically
evaluate the created content paired with human playtesting. Participants in
four different scenarios are asked about their perception of changes made to
the level both before and after balancing, and vice versa. Based on descriptive
and statistical analysis, our findings indicate that the PCGRL-based balancing
positively influences players' perceived balance for most scenarios, albeit
with differences in aspects of the balancing between scenarios.
