机器教育：设计语义有序和本体指导的模块化神经网络
Machine Education: Designing semantically ordered and ontologically guided modular neural networks
摘要：
关于机器教学、机器教育和机器课程设计的文献还处于起步阶段，关于这个主题的论文很少，主要集中在数据和模型工程因素上，以改善机器学习。在本文中，我们首先讨论了迄今为止在机器教学和教育方面的一些尝试。然后，我们将理论和方法从人类教育到结构，并在数学上定义机器教育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，但并非最不重要的是，我们提供了一个基于本体的方法来指导课程计划的开发，以产生透明和可解释的模块化学习机器，包括神经网络。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
