Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/82084
Title: | Game mechanic alignment theory and discovery |
Authors: | Cerny Green, Michael Khalifa, Ahmed Bontrager, Philip Canaan, Rodrigo Togelius, Julian |
Keywords: | Computer games -- Design Artificial intelligence Nonparametric statistics Intelligent tutoring systems |
Issue Date: | 2021 |
Publisher: | Association for Computing Machinery |
Citation: | Cerny Green, M., Khalifa, A., Bontrager, P., Canaan, R., & Togelius, J. (2021). Game mechanic alignment theory and discovery. FDG '21: International Conference on the Foundations of Digital Games, Montreal. |
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. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/82084 |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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Game_mechanic_alignment_theory_and_discovery_2021.pdf Restricted Access | 1.01 MB | Adobe PDF | View/Open Request a copy |
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