| DOI | Resolve DOI: https://doi.org/10.1007/978-3-031-19679-9_63 |
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| Author | Search for: Aziz, Rifah Sama1ORCID identifier: https://orcid.org/0000-0003-3533-0782; Search for: Emond, Bruno1ORCID identifier: https://orcid.org/0000-0003-0901-8293 |
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| Affiliation | - National Research Council Canada. Digital Technologies
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| Format | Text, Article |
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| Conference | 24th International Conference on Human-Computer Interaction, HCII 2022, June 26 – July 1, 2022, Virtual Event |
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| Subject | autonomous agents; virtual reality; pedagogical strategies; reinforcement learning |
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| Abstract | Pedagogical learning among agents have the power to influence the learning of a new learner in several ways. While such pedagogical approaches of student-teacher interactions are applied on popular games with complex environments, we propose the use of pedagogical learning strategies among autonomous agents on a virtual reality (VR) training application in order to automate the existing tutoring system in the application. Creating four reinforcement learning (RL) agents with Q-Learning algorithm, we experiment the agents with different reward functions to choose the best performer as the tutor. We apply the pedagogical strategy with a budget between the tutor and the learner agent resulting in improvements in the learner’s performance. |
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| Publication date | 2022-11-24 |
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| Publisher | Springer Nature Switzerland |
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| In | |
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| Series | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 092abd61-a800-412c-968e-a86ec8f21029 |
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| Record created | 2023-01-20 |
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| Record modified | 2023-01-20 |
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