Video Game Description Language Environment for Unity Machine Learning Agents

Mads Johansen, Martin Pichlmair, Sebastian Risi

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