Uncertainties based queries for Interactive policy learning with evaluations and corrections

Carlos Celemin; Jens Kober

doi:10.1145/3461615.3485404

Uncertainties based queries for Interactive policy learning with evaluations and corrections

Carlos Celemin, Jens Kober

Learning & Autonomous Control

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Original language	English
Title of host publication	Proceeding ICMI 2021 Companion
Subtitle of host publication	Companion Publication of the 2021 International Conference on Multimodal Interaction
Editors	Zakia Hammal, Carlos Busso, Catherine Pelachaud, Sharon Oviatt, Albert Ali Salah, Guoying Zhao
Publisher	Association for Computing Machinery (ACM)
Pages	192-193
Number of pages	2
ISBN (Electronic)	978-1-4503-8471-1
DOIs	https://doi.org/10.1145/3461615.3485404
Publication status	Published - 2021
Event	23rd ACM International Conference on Multimodal Interaction, ICMI 2021 - Virtual, Online, Canada Duration: 18 Oct 2021 → 22 Oct 2021

Conference

Conference	23rd ACM International Conference on Multimodal Interaction, ICMI 2021
Country/Territory	Canada
City	Virtual, Online
Period	18/10/21 → 22/10/21

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

ambiguities
corrective feedback
evaluative feedback
Interactive Learning
uncertainty

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10.1145/3461615.3485404

3461615.3485404Final published version, 608 KB

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Celemin, C., & Kober, J. (2021). Uncertainties based queries for Interactive policy learning with evaluations and corrections. In Z. Hammal, C. Busso, C. Pelachaud, S. Oviatt, A. A. Salah, & G. Zhao (Eds.), Proceeding ICMI 2021 Companion: Companion Publication of the 2021 International Conference on Multimodal Interaction (pp. 192-193). Association for Computing Machinery (ACM). https://doi.org/10.1145/3461615.3485404

Celemin, Carlos ; Kober, Jens. / Uncertainties based queries for Interactive policy learning with evaluations and corrections. Proceeding ICMI 2021 Companion: Companion Publication of the 2021 International Conference on Multimodal Interaction. editor / Zakia Hammal ; Carlos Busso ; Catherine Pelachaud ; Sharon Oviatt ; Albert Ali Salah ; Guoying Zhao. Association for Computing Machinery (ACM), 2021. pp. 192-193

@inproceedings{745928c21e5d4df7b9c00c7956001dfe,

title = "Uncertainties based queries for Interactive policy learning with evaluations and corrections",

keywords = "ambiguities, corrective feedback, evaluative feedback, Interactive Learning, uncertainty",

author = "Carlos Celemin and Jens Kober",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 23rd ACM International Conference on Multimodal Interaction, ICMI 2021 ; Conference date: 18-10-2021 Through 22-10-2021",

year = "2021",

doi = "10.1145/3461615.3485404",

language = "English",

pages = "192--193",

editor = "Zakia Hammal and Busso, {Carlos } and Catherine Pelachaud and Sharon Oviatt and Salah, {Albert Ali} and Zhao, {Guoying }",

booktitle = "Proceeding ICMI 2021 Companion",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

}

Celemin, C & Kober, J 2021, Uncertainties based queries for Interactive policy learning with evaluations and corrections. in Z Hammal, C Busso, C Pelachaud, S Oviatt, AA Salah & G Zhao (eds), Proceeding ICMI 2021 Companion: Companion Publication of the 2021 International Conference on Multimodal Interaction. Association for Computing Machinery (ACM), pp. 192-193, 23rd ACM International Conference on Multimodal Interaction, ICMI 2021, Virtual, Online, Canada, 18/10/21. https://doi.org/10.1145/3461615.3485404

Uncertainties based queries for Interactive policy learning with evaluations and corrections. / Celemin, Carlos; Kober, Jens.
Proceeding ICMI 2021 Companion: Companion Publication of the 2021 International Conference on Multimodal Interaction. ed. / Zakia Hammal; Carlos Busso; Catherine Pelachaud; Sharon Oviatt; Albert Ali Salah; Guoying Zhao. Association for Computing Machinery (ACM), 2021. p. 192-193.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T1 - Uncertainties based queries for Interactive policy learning with evaluations and corrections

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AU - Kober, Jens

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2021

Y1 - 2021

KW - ambiguities

KW - corrective feedback

KW - evaluative feedback

KW - Interactive Learning

KW - uncertainty

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U2 - 10.1145/3461615.3485404

DO - 10.1145/3461615.3485404

M3 - Conference contribution

AN - SCOPUS:85122267087

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EP - 193

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A2 - Pelachaud, Catherine

A2 - Oviatt, Sharon

A2 - Salah, Albert Ali

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PB - Association for Computing Machinery (ACM)

T2 - 23rd ACM International Conference on Multimodal Interaction, ICMI 2021

Y2 - 18 October 2021 through 22 October 2021

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Celemin C, Kober J. Uncertainties based queries for Interactive policy learning with evaluations and corrections. In Hammal Z, Busso C, Pelachaud C, Oviatt S, Salah AA, Zhao G, editors, Proceeding ICMI 2021 Companion: Companion Publication of the 2021 International Conference on Multimodal Interaction. Association for Computing Machinery (ACM). 2021. p. 192-193 doi: 10.1145/3461615.3485404

Uncertainties based queries for Interactive policy learning with evaluations and corrections

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