Data-driven scenario modeling and generation for virtual training system

The rising penetration of virtual training has necessitated the development of meaningful training scenarios to ensure training efficiency. For mission-based virtual training, the scenarios often consist of two common aspects: On the one hand, scenarios are associated with trainer's desired mis...

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Bibliographic Details
Main Author: Yin, Haiyan
Other Authors: Cai Wentong
Format: Final Year Project (FYP)
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/59085
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author Yin, Haiyan
author2 Cai Wentong
author_facet Cai Wentong
Yin, Haiyan
author_sort Yin, Haiyan
collection NTU
description The rising penetration of virtual training has necessitated the development of meaningful training scenarios to ensure training efficiency. For mission-based virtual training, the scenarios often consist of two common aspects: On the one hand, scenarios are associated with trainer's desired mission objectives which specify the tasks or knowledge to be trained on; On the other hand, they are preferred to be customized to individual trainee for an increased training efficiency. However, developing such a scenario is costly, because initializing a scenario that fulfills the desire of both the trainer and the trainee is comprehensive and often requires a certain amount of manual effort. Moreover, scenarios are consumed fast because there often lacks replay-ability. This study aimed to design an automated scenario generation framework for virtual training. The framework involved the trainer's desired mission objectives to control the difficulty of scenario and the trainee's skill levels to realize customization. In addition, a data-driven approach was proposed to improve the evaluation of scenario's difficulty levels. In this approach, player's performance data on the simulation was collected and trained to construct artificial neural networks (ANNs). To facilitate the collection of player's performance data, we also modeled an AI-Player which can imitate the real human player's playing behaviors. We conducted an empirical study on an interactive game with food distribution mission to demonstrate the efficiency of the automated scenario generation framework for virtual training.
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spelling ntu-10356/590852023-03-03T20:47:41Z Data-driven scenario modeling and generation for virtual training system Yin, Haiyan Cai Wentong School of Computer Engineering Parallel and Distributed Computing Centre DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The rising penetration of virtual training has necessitated the development of meaningful training scenarios to ensure training efficiency. For mission-based virtual training, the scenarios often consist of two common aspects: On the one hand, scenarios are associated with trainer's desired mission objectives which specify the tasks or knowledge to be trained on; On the other hand, they are preferred to be customized to individual trainee for an increased training efficiency. However, developing such a scenario is costly, because initializing a scenario that fulfills the desire of both the trainer and the trainee is comprehensive and often requires a certain amount of manual effort. Moreover, scenarios are consumed fast because there often lacks replay-ability. This study aimed to design an automated scenario generation framework for virtual training. The framework involved the trainer's desired mission objectives to control the difficulty of scenario and the trainee's skill levels to realize customization. In addition, a data-driven approach was proposed to improve the evaluation of scenario's difficulty levels. In this approach, player's performance data on the simulation was collected and trained to construct artificial neural networks (ANNs). To facilitate the collection of player's performance data, we also modeled an AI-Player which can imitate the real human player's playing behaviors. We conducted an empirical study on an interactive game with food distribution mission to demonstrate the efficiency of the automated scenario generation framework for virtual training. Bachelor of Engineering (Computer Engineering) 2014-04-22T07:31:45Z 2014-04-22T07:31:45Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59085 en Nanyang Technological University 67 p. application/pdf
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Yin, Haiyan
Data-driven scenario modeling and generation for virtual training system
title Data-driven scenario modeling and generation for virtual training system
title_full Data-driven scenario modeling and generation for virtual training system
title_fullStr Data-driven scenario modeling and generation for virtual training system
title_full_unstemmed Data-driven scenario modeling and generation for virtual training system
title_short Data-driven scenario modeling and generation for virtual training system
title_sort data driven scenario modeling and generation for virtual training system
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
url http://hdl.handle.net/10356/59085
work_keys_str_mv AT yinhaiyan datadrivenscenariomodelingandgenerationforvirtualtrainingsystem