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R. Porzel

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Book Open access Aug 2026

Emotional Beeps and Blinks: Exploring Emotional Expressiveness in Non-Anthropomorphic Robots Through Sound Design and Color

Effective affective communication is essential for collaborative human-robot interaction, as emotional expressions can enhance trust and collaboration with robots. This paper addresses this need by investigating whether a musically-informed sound design or a color-based display is more effective for emotional expressio...

Ayden Janssen, R. Ringe, Lisa Hesselbarth et al. · 0 citations
Review Open access Feb 2025

How metacognitive architectures remember their own thoughts: a systematic scoping review

Findings show that metacognitive experiences may boost system performance and explainability, e.g., via self-repair, and that future research should focus on standardisation and evaluation, and on transferring promising principles to emergent systems.

Robin Nolte, M. Pomarlan, Ayden Janssen et al. · 3 citations
Book Open access Aug 2026

Emotional Beeps and Blinks: Exploring Emotional Expressiveness in Non-Anthropomorphic Robots Through Sound Design and Color

Investigation of whether a musically-informed sound design or a color-based display is more effective for emotional expression in a non-anthropomorphic kitchen assistant robot shows that effectiveness is emotion-dependent.

Ayden Janssen, Rachel Ringe, Lisa Hesselbarth et al. · 0 citations
Review Open access Aug 2026

How metacognitive architectures remember their own thoughts: a systematic scoping review

Metacognition has gained significant attention for its potential to enhance autonomy and adaptability of artificial agents but remains a fragmented field: diverse theories, terminologies, and design choices have led to disjointed developments and limited comparability across systems. Existing overviews remain at a conc...

Robin Nolte, M. Pomarlan, Ayden Janssen et al. · 0 citations
Book Open access Jul 2026

Linguistic Uncertainty Markers for Trust Calibration in AI-Assisted Decision-Making

While participants rated hedged and unhedged AI as equally trustworthy and likely to be correct, they were significantly less likely to follow hedged advice in a binary choice, and how linguistic markers can be used to calibrate user reliance to model certainty is discussed.

Laura Spillner, Johanna Rockstroh, Nina Wenig et al. · 0 citations

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