Video Game Description Language Environment for Unity Machine Learning Agents
- Mads Johansen,
- Martin Pichlmair,
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPublication milestones
- Published - 01/08/2019
Publication status
Published - 01/08/2019
Publisher
IEEE, United StatesISBN (Electronic)
978-1-7281-1884-0Publication IDs
- Scopus: 85073116022
Host publication title
2019 IEEE Conference on Games (CoG)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.
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Citations
17
Captures
28
Access to documents
Related Event
Title
IEEE 1st Conference on Games 2019
Event type
ConferenceDegree of recognition
International eventDate
20/08/2019 - 23/08/2019Location
Queen Mary University of LondonLondonUnited Kingdom
