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Video Game Description Language Environment for Unity Machine Learning Agents

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Publication milestones

  • Published - 01/08/2019

Publication status

Published - 01/08/2019

Publisher

IEEE, United States

ISBN (Electronic)

978-1-7281-1884-0

Publication 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.

Publication metrics

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Citations
17
Captures
28

Access to documents

Final published version, 657.6 KB
License:Unspecified

Related Event

Title

IEEE 1st Conference on Games 2019

Event type

Conference

Degree of recognition

International event

Date

20/08/2019 - 23/08/2019

Location

Queen Mary University of LondonLondonUnited Kingdom