Learning to Blend Computer Game Levels
Full Text: Learning-to-Blend-Computer-Game-Levels.pdf
We present an approach to generate novel computer game levels that blend different game concepts in an unsupervised fashion. Our primary contribution is an analogical reasoning process to construct blends between level design models learned from gameplay videos. The models represent probabilistic relationships between elements in the game. An analogical reasoning process maps features between two models to produce blended models that can then generate new level chunks. As a proof-of-concept we train our system on the classic platformer game Super Mario Bros. due to its highlyregarded and well understood level design. We evaluate the extent to which the models represent stylistic level design knowledge and demonstrate the ability of our system to explain levels that were blended by human expert designers.
Citation
M. Guzdial, M. Riedl. "Learning to Blend Computer Game Levels". International Conference on Computational Creativity (ICCC), (ed: François Pachet, AmÃlcar Cardoso, Vincent Corruble, Fiammetta Ghedini), pp 354-362, June 2016.| Keywords: | |
| Category: | In Conference |
BibTeX
@incollection{Guzdial+Riedl:ICCC16,
author = {Matthew Guzdial and Mark Riedl},
title = {Learning to Blend Computer Game Levels},
Editor = {François Pachet, AmÃlcar Cardoso, Vincent Corruble, Fiammetta
Ghedini},
Pages = {354-362},
booktitle = {International Conference on Computational Creativity (ICCC)},
year = 2016,
}Last Updated: October 30, 2020Submitted by Sabina P
