Canonical cases of learning involve novel observations external to the mind, but learning can also occur through mental processes such as explaining to oneself, mental simulation, analogical comparison, and reasoning. Recent advances in artificial intelligence (AI) reveal that such learning is not restricted to human minds: artificial minds can also self-correct and arrive at new conclusions by engaging in processes of 'learning by thinking' (LbT). How can elements already in the mind generate new knowledge? This article aims to resolve this paradox, and in so doing highlights an important feature of natural and artificial minds – to navigate uncertain environments with variable goals, minds with limited resources must construct knowledge representations 'on demand'. LbT supports this construction.

中文翻译：

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通过自然和人工思维中的思考来学习


典型的学习案例涉及心灵之外的新观察，但学习也可以通过心理过程发生，例如向自己解释、心理模拟、类比比较和推理。人工智能 （AI） 的最新进展表明，这种学习并不局限于人类思维：人工智能还可以通过参与“通过思考学习”（LbT） 的过程进行自我纠正并得出新的结论。大脑中已有的元素如何产生新知识？本文旨在解决这个悖论，并在此过程中强调了自然和人工思维的一个重要特征——为了驾驭具有可变目标的不确定环境，资源有限的大脑必须“按需”构建知识表示。LbT 支持此结构。