Video Game Description Language Environment for Unity Machine Learning Agents

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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:
Original languageEnglish
Title of host publication2019 IEEE Conference on Games (CoG)
Number of pages8
Publication date1 Aug 2019
ISBN (Electronic)978-1-7281-1884-0
Publication statusPublished - 1 Aug 2019
EventIEEE Conference on Games - Queen Mary University of London, London, United Kingdom
Duration: 20 Aug 201923 Aug 2019


ConferenceIEEE Conference on Games
LocationQueen Mary University of London
LandUnited Kingdom


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ID: 84649983