Abstraction and generalization in statistical learning: implications for the relationship between semantic types and episodic tokens
Abstraction and generalization in statistical learning: implications for the relationship between semantic types and episodic tokens
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DOI：
10.1098/rstb.2016.0060
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发表时间：
2017-01-05
影响因子：
6.3
通讯作者：
Altmann, Gerry T. M.
中科院分区：
文献类型：
--
作者：
Altmann, Gerry T. M.
对新兴知识的统计方法倾向于关注单个事件的经验积累成跨事件的概括性经验的过程。然而，这种体验提供了一个看似相反但同样关键的过程：通过这个过程，从一个类型的空间(例如洋葱--通过接触涉及单个洋葱的个别情节而形成的一个语义类别)，我们可以在没有对特定标志的任何先前感知经验的情况下，动态地感知或创造一个特定的标志(一个特定的洋葱，也许是被切碎的那个)。这篇文章回顾了一些统计学习研究，这些研究导致了这样的猜测：这个过程--在语义记忆的基础上产生一个新的情景表征--本身就是一个统计的、实际上是联想的过程。文章的结论是，能够跨单个情节进行统计抽象以形成语义记忆的相同过程也能够从这些语义记忆中生成对应于单个记号的表征，以及关于这些记号的新颖情节事实。统计学习是了解这些支持认知的更深层次过程的窗口。这篇文章是《认知科学中统计学习的新领域》主题的一部分。
Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions-a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process-the generation, on the basis of semantic memory, of a novel episodic representation-is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition.This article is part of the themed issue 'Newfrontiers for statistical learning in the cognitive sciences'.