research-article

General Video Game Level Generation

Authors:

Diego Perez-Liebana,

Simon M. Lucas,

Julian TogeliusAuthors Info & Claims

GECCO '16: Proceedings of the Genetic and Evolutionary Computation Conference 2016

Pages 253 - 259

https://doi.org/10.1145/2908812.2908920

Published: 20 July 2016 Publication History

Abstract

This paper presents a framework and an initial study in general video game level generation, the problem of generating levels for not only a single game but for any game within a specified range. While existing level generators are tailored to a particular game, this new challenge requires generators to take into account the constraints and affordances of games that might not even have been designed when the generator was constructed. The framework presented here builds on the General Video Game AI framework (GVG-AI) and the Video Game Description Language (VGDL), in order to reap synergies from research activities connected to the General Video Game Playing Competition. The framework will also form the basis for a new track of this competition. In addition to the framework, the paper presents three general level generators and an empirical comparison of their qualities.

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https://doi.org/10.1109/TG.2023.3292982
Hu CZhao YLiu J(2024)Game Generation via Large Language Models2024 IEEE Conference on Games (CoG)10.1109/CoG60054.2024.10645597(1-4)Online publication date: 5-Aug-2024
https://doi.org/10.1109/CoG60054.2024.10645597
Hojatoleslami MZamanifar KZojaji Z(2024)GFGDA: general framework for generating dungeons with atmosphereMultimedia Tools and Applications10.1007/s11042-024-18833-583:35(83275-83309)Online publication date: 13-Mar-2024
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Index Terms

General Video Game Level Generation

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Published In

cover image ACM Conferences

GECCO '16: Proceedings of the Genetic and Evolutionary Computation Conference 2016

July 2016

1196 pages

ISBN:9781450342063

DOI:10.1145/2908812

Editor:
Tobias Friedrich
Hasso Plattner Institute
,
General Chair:
Frank Neumann
University of Adelaide
,
Program Chair:
Andrew M. Sutton
Hasso Plattner Institute

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2016

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GECCO '16

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SIGEVO

GECCO '16: Genetic and Evolutionary Computation Conference

July 20 - 24, 2016

Colorado, Denver, USA

Acceptance Rates

GECCO '16 Paper Acceptance Rate 137 of 381 submissions, 36%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

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https://doi.org/10.1109/TG.2023.3292982
Hu CZhao YLiu J(2024)Game Generation via Large Language Models2024 IEEE Conference on Games (CoG)10.1109/CoG60054.2024.10645597(1-4)Online publication date: 5-Aug-2024
https://doi.org/10.1109/CoG60054.2024.10645597
Hojatoleslami MZamanifar KZojaji Z(2024)GFGDA: general framework for generating dungeons with atmosphereMultimedia Tools and Applications10.1007/s11042-024-18833-583:35(83275-83309)Online publication date: 13-Mar-2024
https://doi.org/10.1007/s11042-024-18833-5
Hammady RArnab S(2022)Serious Gaming for Behaviour Change: A Systematic ReviewInformation10.3390/info1303014213:3(142)Online publication date: 8-Mar-2022
https://doi.org/10.3390/info13030142
Salge CAranha CBrightmoore AButler SDe Moura Canaan RCook MGreen MFischer HGuckelsberger CHadley JHerve JJohnson MKybartas QMason DPreuss MSmith TThawonmas RTogelius J(2022)Impressions of the GDMC AI Settlement Generation Challenge in MinecraftProceedings of the 17th International Conference on the Foundations of Digital Games10.1145/3555858.3555940(1-16)Online publication date: 5-Sep-2022
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Salge CHervé J(2022)Automated Isovist Computation for MinecraftProceedings of the 17th International Conference on the Foundations of Digital Games10.1145/3555858.3555921(1-9)Online publication date: 5-Sep-2022
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Gaina RDevlin SLucas SPerez-Liebana D(2022)Rolling Horizon Evolutionary Algorithms for General Video Game PlayingIEEE Transactions on Games10.1109/TG.2021.306028214:2(232-242)Online publication date: Jun-2022
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Sure EWang X(2022)A Deep Reinforcement Learning Agent for General Video Game AI Framework Games2022 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)10.1109/ICAICA54878.2022.9844524(182-186)Online publication date: 24-Jun-2022
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Campos SMorales BNunez A(2022)Open-Source Game Engine & Framework for 2D Game Development2022 IEEE Engineering International Research Conference (EIRCON)10.1109/EIRCON56026.2022.9934816(1-4)Online publication date: 26-Oct-2022
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Anyango JSuleman H(2022)Designing Programming Games for Diversity in Teaching Introductory ProgrammingICT Education10.1007/978-3-030-92858-2_2(19-36)Online publication date: 1-Jan-2022
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