Children acquire complex concepts like dog earlier than simple concepts like brown, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it is easier to infer the meaning of complex concepts than that of simple concepts.

中文翻译：

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学习概念：复杂优先悖论的学习理论解决方案

尽管我们最好的神经科学理论表明，学习前者比学习后者更难，因此，应该花更多时间（马库斯·韦宁），但儿童获得像狗这样的复杂概念比像棕色这样的简单概念更早。这就是复杂优先悖论。我们提出了复杂优先悖论的新解决方案。我们的解决方案建立在 Fei Xu 和 Joshua B. Tenenbaum 的贝叶斯单词学习模型的泛化之上。通过关注概念学习的理性理论，我们表明推断复杂概念的含义比推断简单概念的含义更容易。