Title
A Scenario Generation Framework For Automating Instructional Support In Scenario-Based Training
Keywords
Functional L-systems; Intelligent training; Procedural modeling; Scenario generation
Abstract
Within training, scenario creation can be a long and costly activity. This often results in the same scenarios being re-used. While this can work with new trainees, it does not provide effective training for those using a system for continuing training. In order to provide an easier capability for instruction, the authors are pursuing a line of research in scenario generation. While this includes methods for instructors to build scenarios easily via a manual process, automated approaches for scenario generation are also being investigated. The authors have previously completed efforts in reviewing the needs of a scenario generation system (Martin et al., 2009) and in building a conceptual model for scenarios and how varying complexity can be achieved. This paper provides a review of this work and then presents a computational approach to automated scenario generation. The authors are pursuing research investigating processes and tools for scenario generation, both manual and automated. A recently re-discovered approach (Shape Grammars) and a newly-developed approach (Functional L-systems) each shows great promise for their use in automated scenario generation. However, based on their additional expressive power, the authors have chosen to use Functional L-systems within their software, which will be reviewed. © 2010 SCS.
Publication Date
12-31-2010
Publication Title
Spring Simulation Multiconference 2010, SpringSim'10
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1145/1878537.1878574
Copyright Status
Unknown
Socpus ID
78650600408 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/78650600408
STARS Citation
Martin, Glenn A. and Hughes, Charles E., "A Scenario Generation Framework For Automating Instructional Support In Scenario-Based Training" (2010). Scopus Export 2010-2014. 200.
https://stars.library.ucf.edu/scopus2010/200