Schürmann, Tim ; Beckerle, Philipp (2024)
Personalizing Human-Agent Interaction Through Cognitive Models.
In: Frontiers in Psychology, 2020, 11
doi: 10.26083/tuprints-00015957
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
Cognitive modeling of human behavior has advanced the understanding of underlying processes in several domains of psychology and cognitive science. In this article, we outline how we expect cognitive modeling to improve comprehension of individual cognitive processes in human-agent interaction and, particularly, human-robot interaction (HRI). We argue that cognitive models offer advantages compared to data-analytical models, specifically for research questions with expressed interest in theories of cognitive functions. However, the implementation of cognitive models is arguably more complex than common statistical procedures. Additionally, cognitive modeling paradigms typically have an explicit commitment to an underlying computational theory. We propose a conceptual framework for designing cognitive models that aims to identify whether the use of cognitive modeling is applicable to a given research question. The framework consists of five external and internal aspects related to the modeling process: research question, level of analysis, modeling paradigms, computational properties, and iterative model development. In addition to deriving our framework from a concise literature analysis, we discuss challenges and potentials of cognitive modeling. We expect cognitive models to leverage personalized human behavior prediction, agent behavior generation, and interaction pretraining as well as adaptation, which we outline with application examples from personalized HRI.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Schürmann, Tim ; Beckerle, Philipp |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Personalizing Human-Agent Interaction Through Cognitive Models |
| Sprache: | Englisch |
| Publikationsjahr: | 5 März 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 24 September 2020 |
| Ort der Erstveröffentlichung: | Lausanne |
| Verlag: | Frontiers Media S.A. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Frontiers in Psychology |
| Jahrgang/Volume einer Zeitschrift: | 11 |
| Kollation: | 7 Seiten |
| DOI: | 10.26083/tuprints-00015957 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/15957 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| Kurzbeschreibung (Abstract): | Cognitive modeling of human behavior has advanced the understanding of underlying processes in several domains of psychology and cognitive science. In this article, we outline how we expect cognitive modeling to improve comprehension of individual cognitive processes in human-agent interaction and, particularly, human-robot interaction (HRI). We argue that cognitive models offer advantages compared to data-analytical models, specifically for research questions with expressed interest in theories of cognitive functions. However, the implementation of cognitive models is arguably more complex than common statistical procedures. Additionally, cognitive modeling paradigms typically have an explicit commitment to an underlying computational theory. We propose a conceptual framework for designing cognitive models that aims to identify whether the use of cognitive modeling is applicable to a given research question. The framework consists of five external and internal aspects related to the modeling process: research question, level of analysis, modeling paradigms, computational properties, and iterative model development. In addition to deriving our framework from a concise literature analysis, we discuss challenges and potentials of cognitive modeling. We expect cognitive models to leverage personalized human behavior prediction, agent behavior generation, and interaction pretraining as well as adaptation, which we outline with application examples from personalized HRI. |
| Freie Schlagworte: | personalization, cognitive modeling, human-agent interaction, behavior prediction/generation, interaction adaption |
| ID-Nummer: | Artikel-ID: 561510 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-159570 |
| Zusätzliche Informationen: | This article is part of the Research Topic: Psychological Models for Personalized Human-Computer Interaction (HCI) |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 100 Philosophie und Psychologie > 150 Psychologie 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Mechatronische Systeme im Maschinenbau (IMS) 03 Fachbereich Humanwissenschaften 03 Fachbereich Humanwissenschaften > Institut für Psychologie 03 Fachbereich Humanwissenschaften > Institut für Psychologie > Arbeits- und Ingenieurpsychologie |
| Hinterlegungsdatum: | 05 Mär 2024 13:46 |
| Letzte Änderung: | 06 Mär 2024 09:12 |
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| Zugehörige Links: | |
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| Suche nach Titel in: | TUfind oder in Google |
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