Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/82014
Title: | Mech-Elites : illuminating the mechanic space of GVG-AI |
Authors: | Charity, Megan Cerny Green, Michael Khalifa, Ahmed Togelius, Julian |
Keywords: | Computer games -- Design Level design (Computer science) Artificial intelligence Machine learning |
Issue Date: | 2020 |
Publisher: | Association for Computing Machinery |
Citation: | Charity, M., Cerny Green, M., Khalifa, A., & Togelius, J. (2020). Mech-Elites : illuminating the mechanic space of GVG-AI. FDG '20: International Conference on the Foundations of Digital Games, Bugibba. |
Abstract: | This paper introduces a fully automatic method of mechanic illumination for general video game level generation. Using the Constrained MAP-Elites algorithm and the GVG-AI framework, this system generates the simplest tile based levels that contain specific sets of game mechanics and also satisfy playability constraints. We apply this method to illuminate the mechanic space for four different games in GVG-AI: Zelda, Solarfox, Plants, and RealPortals. With this system, we can generate playable levels that contain different combinations of most of the possible mechanics. These levels can later be used to populate game tutorials that teach players how to use the mechanics of the game. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/82014 |
ISBN: | 9781450388078 |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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Mech-Elites_illuminating_the_mechanic_space_of_GVG-AI_2020.pdf | 832.46 kB | Adobe PDF | View/Open |
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