论文标题
类似人类的活跃学习：模拟人类学习过程的机器
Human-Like Active Learning: Machines Simulating the Human Learning Process
论文作者
论文摘要
尽管最近在多种方法中引入了积极学习来增加学习者参与度的使用，但缺乏经验实验。在这项研究中，我们试图对齐两个实验，以（1）为机器做出假设，（2）经验证实主动学习对学习的影响。在实验1中，我们比较了被动学习形式与主动学习形式的效果。结果表明，积极学习的学习成果比被动学习更大。在基于人类结果的机器实验中，我们模仿了人类的主动学习是一种知识蒸馏的形式。主动学习框架的表现比被动学习框架更好。最后，我们不仅表明我们可以通过人类的实验结果来建立更好的机器训练框架，而且还通过模仿的机器实验来证实人类实验的结果。类似人类的积极学习对学习表现具有至关重要的影响。
Although the use of active learning to increase learners' engagement has recently been introduced in a variety of methods, empirical experiments are lacking. In this study, we attempted to align two experiments in order to (1) make a hypothesis for machine and (2) empirically confirm the effect of active learning on learning. In Experiment 1, we compared the effect of a passive form of learning to active form of learning. The results showed that active learning had a greater learning outcomes than passive learning. In the machine experiment based on the human result, we imitated the human active learning as a form of knowledge distillation. The active learning framework performed better than the passive learning framework. In the end, we showed not only that we can make build better machine training framework through the human experiment result, but also empirically confirm the result of human experiment through imitated machine experiments; human-like active learning have crucial effect on learning performance.
