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Personalizing Human-Agent Interaction Through Cognitive Models

Schürmann, Tim ; Beckerle, Philipp (2024)
Personalizing Human-Agent Interaction Through Cognitive Models.
In: Frontiers in Psychology, 2020, 11
doi: 10.26083/tuprints-00015957
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Personalizing Human-Agent Interaction Through Cognitive Models
Language: English
Date: 5 March 2024
Place of Publication: Darmstadt
Year of primary publication: 24 September 2020
Place of primary publication: Lausanne
Publisher: Frontiers Media S.A.
Journal or Publication Title: Frontiers in Psychology
Volume of the journal: 11
Collation: 7 Seiten
DOI: 10.26083/tuprints-00015957
Corresponding Links:
Origin: Secondary publication DeepGreen
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.

Uncontrolled Keywords: personalization, cognitive modeling, human-agent interaction, behavior prediction/generation, interaction adaption
Identification Number: Artikel-ID: 561510
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-159570
Additional Information:

This article is part of the Research Topic: Psychological Models for Personalized Human-Computer Interaction (HCI)

Classification DDC: 100 Philosophy and psychology > 150 Psychology
600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institute for Mechatronic Systems in Mechanical Engineering (IMS)
03 Department of Human Sciences > Institute for Psychology > Engineering psychology research group!
Date Deposited: 05 Mar 2024 13:46
Last Modified: 11 Jun 2024 14:45
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/15957
PPN: 519038169
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