Human-Centered Cognition Model for Human Digital Twins [* Cross-Reference *]

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Zehnder, Eloïse; Naudet, Yannick, 2026, "Human-Centered Cognition Model for Human Digital Twins [* Cross-Reference *]", https://lore.list.lu/citation?persistentId=perma:LIST.NRD720, LIST Open Repository, V1
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Description
This paper presents an initial proposal for a human-centered cognition model intended to support the development and operation of Human Digital Twins (HDTs). Acknowledging the complexity and incomplete understanding of human cognition, this work adopts a systemic and interdisciplinary approach, integrating perspectives from cognitive sciences, social sciences, engineering, and cognitive informatics. The model aims to formalize the representation of human cognitive dimensions through a structured framework of domains, abilities, and processes, with particular attention to sensation, perception, memory, attention, motor skills, language, metacognition, and higher cognitive functions. Beyond offering a descriptive foundation, the model aspires to facilitate the integration of heterogeneous models and data sources into HDTs, thereby supporting more interpretable, adaptive, and context-aware digital representations of human behavior. While this work does not claim exhaustiveness, it seeks to contribute to ongoing efforts toward a more rigorous and interoperable conceptualization of human cognition within digital twin systems. (2026-01-01)
***This entry has been automatically imported via Infodoc(ASO) CSV by LIST harvest scripts. Please refer to https://doi.org/10.1007/978-3-032-12660-3_20 for the original and latest version of the dataset and data downloads*** (2026-06-04)
Subject Computer and Information Science
Keyword Cognitive Modeling, digital twin, Explainable Artificial Intelligence, interoperability
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