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).
View on arXiv@article{scheibl2025_2503.23760,
title={ Towards a cognitive architecture to enable natural language interaction in co-constructive task learning },
author={ Manuel Scheibl and Birte Richter and Alissa Müller and Michael Beetz and Britta Wrede },
journal={arXiv preprint arXiv:2503.23760},
year={ 2025 }
}