Incremental implicit learning of bundles of statistical patterns.
Incremental implicit learning of bundles of statistical patterns.
复制标题
统计模式束的增量隐式学习。
DOI：
10.1016/j.cognition.2016.09.002
复制
发表时间：
2016
期刊：
影响因子：
3.4
通讯作者：
Aslin,RichardN
中科院分区：
文献类型：
--
作者：
Qian,Ting;Jaeger,TFlorian;Aslin,RichardN
形成任务环境的准确表示通常是逐步进行的，因为与学习表示相关的信息只会随着时间的推移而展开。学习的这种渐进性带来了一个重要的问题：通常不清楚一系列刺激是由单一模式组成，还是由拼接在一起的多个模式组成。在前一种情况下，学习者可以直接使用每个观察到的刺激来不断修改其对任务环境的表征。然而，在后一种情况下，学习者必须首先将刺激序列解析成不同的束，以便不会混淆多个模式。我们创建了一个视频游戏统计学习范式，并调查了(1)在没有预先知道多个刺激束存在的情况下，学习者是否能够检测到它们在输入中的存在，以及(2)学习者是否能够构建丰富的表征，编码与刺激束相关的各种统计模式。通过将人类的学习行为与三个计算模型的预测进行比较，我们发现了学习者能够成功地处理这两个任务的证据。此外，我们还讨论了为什么即使在这种行为看起来非理性的情况下，刺激束的学习也会发生的潜在原因。
Forming an accurate representation of a task environment often takes place incrementally as the information relevant to learning the representation only unfolds over time. This incremental nature of learning poses an important problem: it is usually unclear whether a sequence of stimuli consists of only a single pattern, or multiple patterns that are spliced together. In the former case, the learner can directly use each observed stimulus to continuously revise its representation of the task environment. In the latter case, however, the learner must first parse the sequence of stimuli into different bundles, so as to not conflate the multiple patterns. We created a video-game statistical learning paradigm and investigated (1) whether learners without prior knowledge of the existence of multiple “stimulus bundles” — subsequences of stimuli that define locally coherent statistical patterns — could detect their presence in the input and (2) whether learners are capable of constructing a rich representation that encodes the various statistical patterns associated with bundles. By comparing human learning behavior to the predictions of three computational models, we find evidence that learners can handle both tasks successfully. In addition, we discuss the underlying reasons for why the learning of stimulus bundles occurs even when such behavior may seem irrational.