research-article

The use of functional L-systems for scenario generation in serious games

Authors:

Glenn A. Martin,

Charles E. Hughes,

Denise NicholsonAuthors Info & Claims

PCGames '10: Proceedings of the 2010 Workshop on Procedural Content Generation in Games

Article No.: 6, Pages 1 - 5

https://doi.org/10.1145/1814256.1814262

Published: 18 June 2010 Publication History

Abstract

So called "serious games" have used games (in a sense, virtual environments) for reasons other than entertainment. Particularly within the training community, they have garnered increasing attention over recent years. However, means of generating new scenarios that have increased training effectiveness has continued to be lacking. Because creating new scenarios is a time-intensive and costly exercise. existing scenarios are commonly reused with only minor changes, a practice that can hamper training effectiveness over time.

We have been pursuing a thrust of research in automated scenario generation. In this paper, we present our work in the use of Functional L-systems for generating scenarios. We first review some of our previous work in defining scenarios; then show how Functional L-systems are used to build up the scenarios.

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Digital Library

Cited By

Garn BKieseberg KSchreiber DSimos D(2023)Combinatorial Sequences for Disaster Scenario GenerationOperations Research Forum10.1007/s43069-023-00225-44:2Online publication date: 7-Jun-2023
https://doi.org/10.1007/s43069-023-00225-4
Fontaine MNikolaidis S(2022)Evaluating Human–Robot Interaction Algorithms in Shared Autonomy via Quality Diversity Scenario GenerationACM Transactions on Human-Robot Interaction10.1145/347641211:3(1-30)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1145/3476412
Wen MPark JCho K(2020)A scenario generation pipeline for autonomous vehicle simulatorsHuman-centric Computing and Information Sciences10.1186/s13673-020-00231-z10:1Online publication date: 3-Jun-2020
https://doi.org/10.1186/s13673-020-00231-z
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Index Terms

The use of functional L-systems for scenario generation in serious games
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation support systems
      1. Simulation environments

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cover image ACM Other conferences

PCGames '10: Proceedings of the 2010 Workshop on Procedural Content Generation in Games

June 2010

67 pages

ISBN:9781450300230

DOI:10.1145/1814256

Program Chair:
Rafael Bidarra
Delft University of Technology

Copyright © 2010 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 ACM 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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SASDG: The Society for the Advancement of the Study of Digital Games

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 June 2010

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FDG '10

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SASDG

FDG '10: International Conference on the Foundations of Digital Games

June 18, 2010

California, Monterey

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Overall Acceptance Rate 13 of 15 submissions, 87%

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Cited By

Garn BKieseberg KSchreiber DSimos D(2023)Combinatorial Sequences for Disaster Scenario GenerationOperations Research Forum10.1007/s43069-023-00225-44:2Online publication date: 7-Jun-2023
https://doi.org/10.1007/s43069-023-00225-4
Fontaine MNikolaidis S(2022)Evaluating Human–Robot Interaction Algorithms in Shared Autonomy via Quality Diversity Scenario GenerationACM Transactions on Human-Robot Interaction10.1145/347641211:3(1-30)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1145/3476412
Wen MPark JCho K(2020)A scenario generation pipeline for autonomous vehicle simulatorsHuman-centric Computing and Information Sciences10.1186/s13673-020-00231-z10:1Online publication date: 3-Jun-2020
https://doi.org/10.1186/s13673-020-00231-z
Liapis A(2020)10 Years of the PCG workshop: Past and Future TrendsProceedings of the 15th International Conference on the Foundations of Digital Games10.1145/3402942.3409598(1-10)Online publication date: 15-Sep-2020
https://dl.acm.org/doi/10.1145/3402942.3409598
Luo LYin HCai WZhong JLees M(2017)Design and Evaluation of a Data-Driven Scenario Generation Framework for Game-Based TrainingIEEE Transactions on Computational Intelligence and AI in Games10.1109/TCIAIG.2016.25411689:3(213-226)Online publication date: Sep-2017
https://doi.org/10.1109/TCIAIG.2016.2541168
Hurter JAubrey WMartinez SMaraj CHudson IHuschka TChick S(2016)An analysis of questionnaires and performance measures for a simulation-based kinesic cue detection taskProceedings of the 2016 Winter Simulation Conference10.5555/3042094.3042481(3110-3121)Online publication date: 11-Dec-2016
https://dl.acm.org/doi/10.5555/3042094.3042481
Hurter JAubrey WMartinez SMaraj CHudson I(2016)An analysis of questionnaires and performance measures for a simulation-based kinesic cue detection task2016 Winter Simulation Conference (WSC)10.1109/WSC.2016.7822344(3110-3121)Online publication date: Dec-2016
https://doi.org/10.1109/WSC.2016.7822344
Dey RKonert J(2016)Content Generation for Serious GamesEntertainment Computing and Serious Games10.1007/978-3-319-46152-6_8(174-188)Online publication date: 6-Oct-2016
https://doi.org/10.1007/978-3-319-46152-6_8
Maraj CLackey SBadillo-Urquiola KHudson I(2016)Assessment of Kim’s Game Strategy for Behavior Cue Detection: Engagement, Flow, & Performance AspectsVirtual, Augmented and Mixed Reality10.1007/978-3-319-39907-2_15(156-163)Online publication date: 19-Jun-2016
https://doi.org/10.1007/978-3-319-39907-2_15
Yin HLuo LCai WZhong J(2015)Data-Driven Dynamic Adaptation Framework for Multi-agent Training GameProceedings of the 2015 IEEE / WIC / ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) - Volume 0110.1109/WI-IAT.2015.79(308-311)Online publication date: 6-Dec-2015
https://dl.acm.org/doi/10.1109/WI-IAT.2015.79
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