| アイテムタイプ |
学術雑誌論文 = Journal Article(1) |
| 公開日 |
2025-01-14 |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| タイトル |
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|
タイトル |
A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 著者 |
Hossain, Tahera
Shen, Wanggang
Antar, Anindya
Prabhudesai, Snehal
井上, 創造
Huan, Xun
Banovic, Nikola
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Computational models that formalize complex human behaviors enable study and understanding of such behaviors. However, collecting behavior data required to estimate the parameters of such models is often tedious and resource intensive. Thus, estimating dataset size as part of data collection planning (also known as Sample Size Determination) is important to reduce the time and effort of behavior data collection while maintaining an accurate estimate of model parameters. In this article, we present a sample size determination method based on Uncertainty Quantification (UQ) for a specific Inverse Reinforcement Learning (IRL) model of human behavior, in two cases: (1) pre-hoc experiment design—conducted in the planning stage before any data is collected, to guide the estimation of how many samples to collect; and (2) post-hoc dataset analysis—performed after data is collected, to decide if the existing dataset has sufficient samples and whether more data is needed. We validate our approach in experiments with a realistic model of behaviors of people with Multiple Sclerosis (MS) and illustrate how to pick a reasonable sample size target. Our work enables model designers to perform a deeper, principled investigation of the effects of dataset size on IRL model parameters. |
|
言語 |
en |
| 書誌情報 |
en : ACM Transactions on Computer-Human Interaction
巻 30,
号 1,
p. 1-27,
発行日 2023-03-07
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| 出版社 |
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出版者 |
ACM |
| DOI |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1145/3551388 |
| ISSN |
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収録物識別子タイプ |
PISSN |
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収録物識別子 |
1073-0516 |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
1557-7325 |
| 著作権関連情報 |
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権利情報 |
Copyright (c) ACM 2023. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Computer-Human Interaction, https://doi.org/10.1145/3551388. |
| 出版タイプ |
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出版タイプ |
AM |
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出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| 査読の有無 |
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|
値 |
yes |
| 研究者情報 |
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|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html |
| 論文ID（連携） |
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|
値 |
10409535 |
| 連携ID |
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値 |
11330 |
10409535.pdf (2.1 MB)
