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Video Game Description Language Environment for Unity Machine Learning Agents

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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Video Game Description Language Environment for Unity Machine Learning Agents. / Johansen, Mads; Pichlmair, Martin; Risi, Sebastian.

2019 IEEE Conference on Games (CoG). IEEE, 2019.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Johansen, M, Pichlmair, M & Risi, S 2019, Video Game Description Language Environment for Unity Machine Learning Agents. in 2019 IEEE Conference on Games (CoG). IEEE, IEEE Conference on Games, London, United Kingdom, 20/08/2019. https://doi.org/10.1109/CIG.2019.8848072

APA

Vancouver

Author

Bibtex

@inproceedings{911c6c3c967b40f096690bc18ae75b5b,
title = "Video Game Description Language Environment for Unity Machine Learning Agents",
abstract = "This paper introduces UnityVGDL, a port of the Video Game Description Language (VGDL) to the widely used Unity game engine. Our framework is based on the General Video Game AI (GVGAI) competition framework and implements its core ontology, including a forward model. It integrates the Unity Machine Learning Agents (ML-Agents) toolkit with VGDL to train and run agents in VGDL-described games. We compare baseline learning results between GVGAI and UnityVGDL across four different games and conclude that the Unity port is comparable to the GVGAI framework. UnityVGDL is available at: https://github.com/pyjamads/UnityVGDL.",
author = "Mads Johansen and Martin Pichlmair and Sebastian Risi",
note = "Mangler OA-fil /PFOR 04-11-2019; IEEE Conference on Games, IEEE COG ; Conference date: 20-08-2019 Through 23-08-2019",
year = "2019",
month = aug
day = "1",
doi = "10.1109/CIG.2019.8848072",
language = "English",
booktitle = "2019 IEEE Conference on Games (CoG)",
publisher = "IEEE",
address = "United States",
url = "http://www.ieee-cog.org",

}

RIS

TY - GEN

T1 - Video Game Description Language Environment for Unity Machine Learning Agents

AU - Johansen, Mads

AU - Pichlmair, Martin

AU - Risi, Sebastian

N1 - Mangler OA-fil /PFOR 04-11-2019

PY - 2019/8/1

Y1 - 2019/8/1

N2 - This paper introduces UnityVGDL, a port of the Video Game Description Language (VGDL) to the widely used Unity game engine. Our framework is based on the General Video Game AI (GVGAI) competition framework and implements its core ontology, including a forward model. It integrates the Unity Machine Learning Agents (ML-Agents) toolkit with VGDL to train and run agents in VGDL-described games. We compare baseline learning results between GVGAI and UnityVGDL across four different games and conclude that the Unity port is comparable to the GVGAI framework. UnityVGDL is available at: https://github.com/pyjamads/UnityVGDL.

AB - This paper introduces UnityVGDL, a port of the Video Game Description Language (VGDL) to the widely used Unity game engine. Our framework is based on the General Video Game AI (GVGAI) competition framework and implements its core ontology, including a forward model. It integrates the Unity Machine Learning Agents (ML-Agents) toolkit with VGDL to train and run agents in VGDL-described games. We compare baseline learning results between GVGAI and UnityVGDL across four different games and conclude that the Unity port is comparable to the GVGAI framework. UnityVGDL is available at: https://github.com/pyjamads/UnityVGDL.

U2 - 10.1109/CIG.2019.8848072

DO - 10.1109/CIG.2019.8848072

M3 - Article in proceedings

BT - 2019 IEEE Conference on Games (CoG)

PB - IEEE

T2 - IEEE Conference on Games

Y2 - 20 August 2019 through 23 August 2019

ER -

ID: 84649983