Game Mechanic Alignment Theory and Discovery
Green, Michael Cerny, Khalifa, Ahmed, Bontrager, Philip, Canaan, Rodrigo, Togelius, Julian
–arXiv.org Artificial Intelligence
We present a new concept called Game Mechanic Alignment theory as a way to organize game mechanics through the lens of environmental rewards and intrinsic player motivations. By disentangling player and environmental influences, mechanics may be better identified for use in an automated tutorial generation system, which could tailor tutorials for a particular playstyle or player. Within, we apply this theory to several well-known games to demonstrate how designers can benefit from it, we describe a methodology for how to estimate mechanic alignment, and we apply this methodology on multiple games in the GVGAI framework. We discuss how effectively this estimation captures intrinsic/extrinsic rewards and how our theory could be used as an alternative to critical mechanic discovery methods for tutorial generation.
arXiv.org Artificial Intelligence
Feb-19-2021
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- Information Technology > Artificial Intelligence