论文标题
机器教育：设计语义上有序和本体学指导的模块化神经网络
Machine Education: Designing semantically ordered and ontologically guided modular neural networks
论文作者
论文摘要
有关机器的机器教学，机器教育和课程设计的文献尚处于起步阶段，其主题的稀疏论文主要关注数据和模型工程因素，以改善机器学习。在本文中，我们首先讨论了有关机器教学和教育的选定尝试。然后，我们将理论和方法从人类教育到结构，并在数学上定义了机器教育的课程设计中的核心问题以及支持机器教育步骤所需的建模方法。最后但并非最不重要的一点是，我们提供了一种基于本体的方法来指导开发课程计划，以生成包括神经网络在内的透明和可解释的模块化学习机。
The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning. In this paper, we first discuss selected attempts to date on machine teaching and education. We then bring theories and methodologies together from human education to structure and mathematically define the core problems in lesson design for machine education and the modelling approaches required to support the steps for machine education. Last, but not least, we offer an ontology-based methodology to guide the development of lesson plans to produce transparent and explainable modular learning machines, including neural networks.
