Game Mechanic Alignment Theory and Discovery

TL;DR

This paper introduces Game Mechanic Alignment theory to categorize game mechanics based on systemic rewards and player motivations, aiding automated tutorial generation and game design analysis.

Contribution

It proposes a novel theoretical framework and methodology for estimating mechanic alignment, demonstrated through applications to multiple games in the GVGAI framework.

Findings

Mechanic alignment estimation correlates with player motivations.

The theory helps identify mechanics suitable for personalized tutorials.

Application to GVGAI games shows practical utility.

Abstract

We present a new concept called Game Mechanic Alignment theory as a way to organize game mechanics through the lens of systemic rewards and agential motivations. By disentangling player and systemic 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 agential motivations and systemic rewards and how our theory could be used as an alternative way to find mechanics for tutorial generation.