În afara temei aiqbench
Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.
Toward an~Integrated Cognitive--Ergonomic Architecture for~Human--Machine Interaction: Combining Cognitive Models with~Human Factors Ergonomics
arXiv:2609.03704v1 Announce Type: new Abstract: This paper presents an integrated approach to modeling human competencies by combining the theoretical foundations of cognitive architectures with principles from Human Factors Ergonomics (HFE). Through a comparative analysis of established cognitive models-SOAR, ACT-R, LIDA, and COCOM-we synthesize a tailored architecture designed to address the complexities of human-machine interaction (HMI) in dynamic environments. By contextualizing this model within ergonomic frameworks, we elucidate the mechanisms underlying decision-making, skill acquisition, and adaptive behavior, bridging the gap between cognitive theory and applied system design. Our framework is empirically grounded in industrial robotics applications, where operator expertise, normative knowledge, and real-time feedback loops are critical. The proposed architecture not only enhances the cognitive alignment of HMI systems but also provides a scalable methodology for designing intelligent, human-centered interfaces in high-stakes environments. This work advances both the theoretical understanding of human competencies and the practical implementation of adaptive, ergonomically optimized systems.
Abstract:This paper presents an integrated approach to modeling human competencies by combining the theoretical foundations of cognitive architectures with principles from Human Factors Ergonomics (HFE). Through a comparative analysis of established cognitive models-SOAR, ACT-R, LIDA, and COCOM-we synthesize a tailored architecture designed to address the complexities of human-machine interaction (HMI) in dynamic environments. By contextualizing this model within ergonomic frameworks, we elucidate the mechanisms underlying decision-making, skill acquisition, and adaptive behavior, bridging the gap between cognitive theory and applied system design. Our framework is empirically grounded in industrial robotics applications, where operator expertise, normative knowledge, and real-time feedback loops are critical. The proposed architecture not only enhances the cognitive alignment of HMI systems but also provides a scalable methodology for designing intelligent, human-centered interfaces in high-stakes environments. This work advances both the theoretical understanding of human competencies and the practical implementation of adaptive, ergonomically optimized systems.
Robotics (cs.RO)
arXiv:2609.03704 [cs.RO]
(or arXiv:2609.03704v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.03704 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
28th International Conference on Human-Computer interaction, Jul 2026, Montr{é}al (Qu{é}bec), Canada. pp.191-200
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Text integral sub licența deschisă a publicației · 251 cuvinte
Subiecte conexe

Presentation: From Hype to Strong Foundations: What the Rise, Fall and Resurgence of Agents Can Teach Us About Outlasting the Cycle
InfoQ · 17 iun. 2026
Assessing Information Ecosystems : How Governments Can Get Ahead of Hybrid Threats
carnegieendowment.org · 5 aug. 2026

Artmarket.com: H1 2026 Financial Report -- One-of-a - Kind AI Systems Intuitive Artmarket and Blind Spot Will Drive the Next Phase of Growth for
australiannews.net · 29 sept. 2026
Artmarket.com: H1 2026 Financial Report -- One-of-a - Kind AI Systems Intuitive Artmarket® and Blind Spot Will Drive the Next Phase of Growth for AI - First Artprice in 2026 - 2030
thailand-business-news.com · 28 sept. 2026