Engagement in Human-Agent Interaction: An Overview.

engagement engagement generation engagement perception human-agent interaction (HAI) human-robot interaction (HRI)

Journal

Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350

Informations de publication

Date de publication:
2020
Historique:
received: 12 03 2020
accepted: 08 06 2020
entrez: 27 1 2021
pubmed: 28 1 2021
medline: 28 1 2021
Statut: epublish

Résumé

Engagement is a concept of the utmost importance in human-computer interaction, not only for informing the design and implementation of interfaces, but also for enabling more sophisticated interfaces capable of adapting to users. While the notion of engagement is actively being studied in a diverse set of domains, the term has been used to refer to a number of related, but different concepts. In fact it has been referred to across different disciplines under different names and with different connotations in mind. Therefore, it can be quite difficult to understand what the meaning of engagement is and how one study relates to another one accordingly. Engagement has been studied not only in human-human, but also in human-agent interactions i.e., interactions with physical robots and embodied virtual agents. In this overview article we focus on different factors involved in engagement studies, distinguishing especially between those studies that address task and social engagement, involve children and adults, are conducted in a lab or aimed for long term interaction. We also present models for detecting engagement and for generating multimodal behaviors to show engagement.

Identifiants

pubmed: 33501259
doi: 10.3389/frobt.2020.00092
pmc: PMC7806067
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

92

Informations de copyright

Copyright © 2020 Oertel, Castellano, Chetouani, Nasir, Obaid, Pelachaud and Peters.

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Auteurs

Catharine Oertel (C)

Interactive Intelligence, Intelligent Systems, EWI, Delft University of Technology, Delft, Netherlands.

Ginevra Castellano (G)

Uppsala Social Robotics Lab, Department of Information Technology, Uppsala University, Uppsala, Sweden.

Mohamed Chetouani (M)

Institute for Intelligent Systems and Robotics, CNRS UMR 7222, Sorbonne University, Paris, France.

Jauwairia Nasir (J)

Computer-Human Interaction in Learning and Instruction Lab, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

Mohammad Obaid (M)

Interaction Design Division, Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.

Catherine Pelachaud (C)

CNRS, Institute for Intelligent Systems and Robotics, Sorbonne University, Paris, France.

Christopher Peters (C)

Embodied Social Agents Lab (ESAL), School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Classifications MeSH