Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns

Emma M. van Zoelen; Karel van den Bosch; David Abbink; Mark Neerincx

doi:10.1007/978-3-031-21203-1_40

Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns

Emma M. van Zoelen^*, Karel van den Bosch, David Abbink, Mark Neerincx

^*Corresponding author for this work

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

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Abstract

When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of collaboration in a commonly shared language, and can communicate with each other about these patterns. For this, we developed an ontology of Collaboration Patterns. An accompanying Graphical User Interface (GUI) enables partners to formalize and refine Collaboration Patterns, which can then be communicated to the partner. The ontology was evaluated empirically with human participants who viewed video recordings of joint human-agent activities. Participants were requested to identify Collaboration Patterns in the footage, and to formalize patterns by using the ontology’s GUI. Results show that the ontology supports humans to recognize and define Collaboration Patterns successfully. To improve the ontology, it is suggested to include pre- and post-conditions of tasks, as well as parallel actions of team members.

Original language	English
Title of host publication	PRIMA 2022
Subtitle of host publication	Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings
Editors	Reyhan Aydoğan, Natalia Criado, Victor Sanchez-Anguix, Jérôme Lang, Marc Serramia
Publisher	Springer
Pages	621-629
Number of pages	9
ISBN (Print)	9783031212024
DOIs	https://doi.org/10.1007/978-3-031-21203-1_40
Publication status	Published - 2023
Event	24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020 - Valencia , Spain Duration: 16 Nov 2022 → 18 Nov 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13753 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020
Country/Territory	Spain
City	Valencia
Period	16/11/22 → 18/11/22

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

Co-learning
Collaboration Patterns
Human-agent team
Ontology

Access to Document

10.1007/978-3-031-21203-1_40

978-3-031-21203-1_40Final published version, 585 KB

Cite this

van Zoelen, E. M., van den Bosch, K., Abbink, D., & Neerincx, M. (2023). Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns. In R. Aydoğan, N. Criado, V. Sanchez-Anguix, J. Lang, & M. Serramia (Eds.), PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings (pp. 621-629). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13753 LNAI). Springer. https://doi.org/10.1007/978-3-031-21203-1_40

van Zoelen, Emma M. ; van den Bosch, Karel ; Abbink, David et al. / Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns. PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings. editor / Reyhan Aydoğan ; Natalia Criado ; Victor Sanchez-Anguix ; Jérôme Lang ; Marc Serramia. Springer, 2023. pp. 621-629 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns",

abstract = "When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of collaboration in a commonly shared language, and can communicate with each other about these patterns. For this, we developed an ontology of Collaboration Patterns. An accompanying Graphical User Interface (GUI) enables partners to formalize and refine Collaboration Patterns, which can then be communicated to the partner. The ontology was evaluated empirically with human participants who viewed video recordings of joint human-agent activities. Participants were requested to identify Collaboration Patterns in the footage, and to formalize patterns by using the ontology{\textquoteright}s GUI. Results show that the ontology supports humans to recognize and define Collaboration Patterns successfully. To improve the ontology, it is suggested to include pre- and post-conditions of tasks, as well as parallel actions of team members.",

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note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – 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. ; 24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020 ; Conference date: 16-11-2022 Through 18-11-2022",

year = "2023",

doi = "10.1007/978-3-031-21203-1_40",

language = "English",

isbn = "9783031212024",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "621--629",

editor = "Reyhan Aydoğan and Natalia Criado and Victor Sanchez-Anguix and J{\'e}r{\^o}me Lang and Marc Serramia",

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van Zoelen, EM, van den Bosch, K, Abbink, D & Neerincx, M 2023, Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns. in R Aydoğan, N Criado, V Sanchez-Anguix, J Lang & M Serramia (eds), PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13753 LNAI, Springer, pp. 621-629, 24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020, Valencia , Spain, 16/11/22. https://doi.org/10.1007/978-3-031-21203-1_40

Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns. / van Zoelen, Emma M.; van den Bosch, Karel; Abbink, David et al.
PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings. ed. / Reyhan Aydoğan; Natalia Criado; Victor Sanchez-Anguix; Jérôme Lang; Marc Serramia. Springer, 2023. p. 621-629 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13753 LNAI).

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

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AU - van Zoelen, Emma M.

AU - van den Bosch, Karel

AU - Abbink, David

AU - Neerincx, Mark

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 - 2023

Y1 - 2023

N2 - When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of collaboration in a commonly shared language, and can communicate with each other about these patterns. For this, we developed an ontology of Collaboration Patterns. An accompanying Graphical User Interface (GUI) enables partners to formalize and refine Collaboration Patterns, which can then be communicated to the partner. The ontology was evaluated empirically with human participants who viewed video recordings of joint human-agent activities. Participants were requested to identify Collaboration Patterns in the footage, and to formalize patterns by using the ontology’s GUI. Results show that the ontology supports humans to recognize and define Collaboration Patterns successfully. To improve the ontology, it is suggested to include pre- and post-conditions of tasks, as well as parallel actions of team members.

AB - When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of collaboration in a commonly shared language, and can communicate with each other about these patterns. For this, we developed an ontology of Collaboration Patterns. An accompanying Graphical User Interface (GUI) enables partners to formalize and refine Collaboration Patterns, which can then be communicated to the partner. The ontology was evaluated empirically with human participants who viewed video recordings of joint human-agent activities. Participants were requested to identify Collaboration Patterns in the footage, and to formalize patterns by using the ontology’s GUI. Results show that the ontology supports humans to recognize and define Collaboration Patterns successfully. To improve the ontology, it is suggested to include pre- and post-conditions of tasks, as well as parallel actions of team members.

KW - Co-learning

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KW - Human-agent team

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DO - 10.1007/978-3-031-21203-1_40

M3 - Conference contribution

AN - SCOPUS:85142677289

SN - 9783031212024

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 629

BT - PRIMA 2022

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A2 - Criado, Natalia

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van Zoelen EM, van den Bosch K, Abbink D , Neerincx M. Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns. In Aydoğan R, Criado N, Sanchez-Anguix V, Lang J, Serramia M, editors, PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings. Springer. 2023. p. 621-629. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-21203-1_40

Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns

Abstract

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