AAAI Publications, Ninth Artificial Intelligence and Interactive Digital Entertainment Conference

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Mission-Based Scenario Modeling and Generation for Virtual Training
Linbo Luo, Haiyan Yin, Jinghui Zhong, Wentong Cai, Michael Lees, Suiping Zhou

Last modified: 2013-11-13


Automated scenario generation for virtual training has become an emerging research problem, as manual authoring is often time consuming and costly. In this paper, we present a mission-based scenario modeling and generation framework for virtual training. In particular, we consider the issue of how the timing of the events in a scenario can impact the training process and how to incorporate such impact into the scenario generation. To this end, our framework is designed to explicitly capture the propagated effect of an event and its influence to other events. For representing mission-based scenarios, the concepts of mission objectives, events, and scenario beats are introduced. The generation process is designed to generate scenarios that can tailor to trainer's preference and adapt to different trainees' skill levels. The efficacy of the proposed framework is demonstrated through an empirical study of human players in a food distribution training game.


Scenario Generation; Training; Serious Games

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