GAIG Game AI Research Group @ QMUL

PlayMapper: Illuminating Design Spaces of Platform Games

2019
Warriar, Vivek R and Ugarte, Carmen and Woodward, John R and Tokarchuk, Laurissa

Abstract

In this paper, we present PlayMapper, a novel variant of the MAP-Elites algorithm that has been adapted to map the level design space of the Super Mario Bros game. Our approach uses player and level based features to create a map of playable levels. We conduct an experiment to compare the effect of different sets of input features on the range of levels generated using this technique. In this work, we show that existing search-based techniques for PCG can be improved to allow for more control and creative freedom for designers. Current limitations of the system and directions for future work are also discussed.
URL: https://ieeexplore.ieee.org/document/8848118

Cite this work

@inproceedings{warriar2019playmapper,
author= {Warriar, Vivek R and Ugarte, Carmen and Woodward, John R and Tokarchuk, Laurissa},
title= {{PlayMapper: Illuminating Design Spaces of Platform Games}},
year= {2019},
booktitle= {{IEEE Conference on Games (COG)}},
pages= {1--8},
url= {https://ieeexplore.ieee.org/document/8848118},
abstract= {In this paper, we present PlayMapper, a novel variant of the MAP-Elites algorithm that has been adapted to map the level design space of the Super Mario Bros game. Our approach uses player and level based features to create a map of playable levels. We conduct an experiment to compare the effect of different sets of input features on the range of levels generated using this technique. In this work, we show that existing search-based techniques for PCG can be improved to allow for more control and creative freedom for designers. Current limitations of the system and directions for future work are also discussed.},
}

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