Abstract Research towards a new approach to the abstract symbol grounding problem showed that through model counting there is a correspondence between logical/linguistic and coordinate representation in the visuospatial domain. The logical/verbal description of a spatial layout directly gives rise to a coordinate representation that can be drawn, with the drawing reflecting what is described. The main characteristic of this logical property is that it does not need any semantic information or ontology apart from a separation into symbols/words referring to relations and symbols/words referring to objects. Moreover, the complete mechanism can be implemented efficiently on a brain inspired cognitive architecture, the Activation Bit Vector Machine (ABVM), an architecture that belongs to the Vector Symbolic Architectures. However, the natural language fragment captured previously was restricted to simple predication sentences, with the corresponding logical fragment being atomic Context Logic (CLA), and the only actuation modality leveraged was visualization. This article extends the approach on all three aspects: adding a third category of action verbs we move to a fragment of first-order Context Logic (CL1), with modalities requiring a temporal dimension, such as film and music, becoming available. The article presents an ABVM generating sequences of images from texts.

中文翻译：

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使用激活位向量机进行多模式驱动

摘要 针对抽象符号接地问题的一种新方法的研究表明，通过模型计数，视觉空间域中的逻辑/语言和坐标表示之间存在对应关系。空间布局的逻辑/语言描述直接产生可以绘制的坐标表示，而绘图反映了所描述的内容。这个逻辑属性的主要特征是它不需要任何语义信息或本体，除了分离成指代关系的符号/词和指代对象的符号/词。此外，完整的机制可以在受大脑启发的认知架构上有效实现，即激活位向量机 (ABVM)，该架构属于向量符号架构。然而，之前捕获的自然语言片段仅限于简单的谓词句子，相应的逻辑片段是原子上下文逻辑 (CLA)，唯一利用的驱动方式是可视化。本文扩展了所有三个方面的方法：添加第三类动作动词，我们将其移至一阶上下文逻辑 (CL1) 的片段，需要时间维度的模态，例如电影和音乐，变得可用。本文介绍了一种从文本生成图像序列的 ABVM。添加第三类动作动词，我们将移动到一阶上下文逻辑 (CL1) 的片段中，需要时间维度的模态，例如电影和音乐，变得可用。本文介绍了一种从文本生成图像序列的 ABVM。添加第三类动作动词，我们将移动到一阶上下文逻辑 (CL1) 的片段中，需要时间维度的模态，例如电影和音乐，变得可用。本文介绍了一种从文本生成图像序列的 ABVM。