Learning to tutor from expert demonstrators via apprenticeship scheduling
We have conducted a study investigating the use of automated tutors for educating players in the context of serious gaming (i.e., game designed as a professional training tool). Historically, researchers and practitioners have developed automated tutors through a process of manually codifying domain...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for the Advancement of Artificial Intelligence
2020
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| Online Access: | https://hdl.handle.net/1721.1/125135 |
| _version_ | 1811091042276999168 |
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| author | Gombolay, Matthew Jensen, Reed Stigile, Jessica Son, Sung-Hyun Shah, Julie |
| author2 | Lincoln Laboratory |
| author_facet | Lincoln Laboratory Gombolay, Matthew Jensen, Reed Stigile, Jessica Son, Sung-Hyun Shah, Julie |
| author_sort | Gombolay, Matthew |
| collection | MIT |
| description | We have conducted a study investigating the use of automated tutors for educating players in the context of serious gaming (i.e., game designed as a professional training tool). Historically, researchers and practitioners have developed automated tutors through a process of manually codifying domain knowledge and translating that into a human-interpretable format. This process is laborious and leaves much to be desired. Instead, we seek to apply novel machine learning tech-niques to, first, leam a model from domain experts' demonstrations how to solve such problems, and, second, use this model to teach novices how to think like experts. In this work, we present a study comparing the performance of an automated and a traditional, manually-constructed tutor. To our knowledge, this is the first investigation using learning from demonstration techniques to learn from experts and use that knowledge to teach novices. |
| first_indexed | 2024-09-23T14:56:12Z |
| format | Article |
| id | mit-1721.1/125135 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T14:56:12Z |
| publishDate | 2020 |
| publisher | Association for the Advancement of Artificial Intelligence |
| record_format | dspace |
| spelling | mit-1721.1/1251352022-10-01T23:28:02Z Learning to tutor from expert demonstrators via apprenticeship scheduling Gombolay, Matthew Jensen, Reed Stigile, Jessica Son, Sung-Hyun Shah, Julie Lincoln Laboratory Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory We have conducted a study investigating the use of automated tutors for educating players in the context of serious gaming (i.e., game designed as a professional training tool). Historically, researchers and practitioners have developed automated tutors through a process of manually codifying domain knowledge and translating that into a human-interpretable format. This process is laborious and leaves much to be desired. Instead, we seek to apply novel machine learning tech-niques to, first, leam a model from domain experts' demonstrations how to solve such problems, and, second, use this model to teach novices how to think like experts. In this work, we present a study comparing the performance of an automated and a traditional, manually-constructed tutor. To our knowledge, this is the first investigation using learning from demonstration techniques to learn from experts and use that knowledge to teach novices. 2020-05-08T14:50:23Z 2020-05-08T14:50:23Z 2017-03 2019-10-31T14:57:48Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/125135 Gombolay, Matthew et al. "Learning to tutor from expert demonstrators via apprenticeship scheduling." Workshops at the Thirty-First AAAI Conference on Artificial Intelligence (March 2017): 664-669 © 2017 Association for the Advancement of Artificial Intelligence en https://www.aaai.org/ocs/index.php/WS/AAAIW17/paper/view/15098 Workshops at the Thirty-First AAAI Conference on Artificial Intelligence Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for the Advancement of Artificial Intelligence MIT web domain |
| spellingShingle | Gombolay, Matthew Jensen, Reed Stigile, Jessica Son, Sung-Hyun Shah, Julie Learning to tutor from expert demonstrators via apprenticeship scheduling |
| title | Learning to tutor from expert demonstrators via apprenticeship scheduling |
| title_full | Learning to tutor from expert demonstrators via apprenticeship scheduling |
| title_fullStr | Learning to tutor from expert demonstrators via apprenticeship scheduling |
| title_full_unstemmed | Learning to tutor from expert demonstrators via apprenticeship scheduling |
| title_short | Learning to tutor from expert demonstrators via apprenticeship scheduling |
| title_sort | learning to tutor from expert demonstrators via apprenticeship scheduling |
| url | https://hdl.handle.net/1721.1/125135 |
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