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).

翻译：本研究探讨了认知架构应具备哪些特性，才能充分利用自然语言在协同建构式任务学习中的优势。为提供背景，我们首先讨论了交互式任务学习、人类记忆系统的运作机制，以及自然语言与多模态交互的重要性。接着，我们审视了认知架构的研究现状，通过分析其现有能力，提出了一个基于多源依据的协同建构式任务学习概念。随后，我们整合了来自不同研究领域的洞见，构建出一个统一的理论框架。最后，我们总结了当前面临的挑战以及实现人机交互中协同建构式任务学习所需满足的关键要求。