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by Irene M. Gironacci
| Institution: | Swinburne |
|---|---|
| Department: | Theses |
| Degree: | |
| Year: | 2022 |
| Keywords: | none |
| Posted: | 3/25/2025 |
| Record ID: | 2222559 |
| Full text PDF: | http://hdl.handle.net/10.25916/sut.26282290.v1 |
Existing XR simulations use pre-configured scenarios in which the trainee always experiences the same training, without any variation or personalization to suit the needs or background and behaviour of the trainee. This research intends to contribute to the existing knowledge in the field of AI-driven narrative exploring how training simulators could evolve towards an interactive and dynamic narrative experience, by integrating Artificial Intelligence in an Extended Reality training simulator. In particular, the simulator uses a Content-Based recommender system to recommend training scenarios to the user. Although customization can be achieved in many ways, this project focuses on in-game input data: user interaction with virtual objects, decisions made by the user, and metadata associated with the training scenario.
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