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arXiv · 2503.23760

Towards a cognitive architecture to enable natural language interaction in co-constructive task learning

Manuel Scheibl·Birte Richter·Alissa Müller·Michael Beetz·Britta Wrede
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Abstract

This research addresses the question, which characteristics a cognitive architecture must have to leverage the benefits of natural language in Co-Constructive Task Learning (CCTL). To provide context, we first discuss Interactive Task Learning (ITL), the mechanisms of the human memory system, and the significance of natural language and multi-modality. Next, we examine the current state of cognitive architectures, analyzing their capabilities to inform a concept of CCTL grounded in multiple sources. We then integrate insights from various research domains to develop a unified framework. Finally, we conclude by identifying the remaining challenges and requirements necessary to achieve CCTL in Human-Robot Interaction (HRI).

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Manuel Scheibl, Birte Richter, Alissa Müller, Michael Beetz, Britta Wrede. 2025-03-31. Towards a cognitive architecture to enable natural language interaction in co-constructive task learning. https://arxiv.org/abs/2503.23760

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