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Recent years, there has been growing interests in experience-drivenprocedural level generation. Various metrics have been formulated to modelplayer experience and help generate personalised levels. In this work, wequestion whether experience metrics can adapt to agents with differentpersonas. We start by reviewing existing metrics for evaluating game levels.Then, focusing on platformer games, we design a framework integrating variousagents and evaluation metrics. Experimental studies on \emph{Super Mario Bros.}indicate that using the same evaluation metrics but agents with differentpersonas can generate levels for particular persona. It implies that, forsimple games, using a game-playing agent of specific player archetype as alevel tester is probably all we need to generate levels of diverse behaviourengagement.

Generating Game Levels of Diverse Behaviour Engagement