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思维如何构建结构:动作序列的分层学习

How the Mind Creates Structure: Hierarchical Learning of Action Sequences.

作者信息

Eckstein Maria K, Collins Anne G E

机构信息

Department of Psychology, 2121 Berkeley Way West, Berkeley, California 94720, USA.

出版信息

Cogsci. 2021 Jul;43:618-624.

Abstract

Humans have the astonishing capacity to quickly adapt to varying environmental demands and reach complex goals in the absence of extrinsic rewards. Part of what underlies this capacity is the ability to flexibly reuse and recombine previous experiences, and to plan future courses of action in a psychological space that is shaped by these experiences. Decades of research have suggested that humans use hierarchical representations for efficient planning and flexibility, but the origin of these representations has remained elusive. This study investigates how 73 participants learned hierarchical representations through experience, in a task in which they had to perform complex action sequences to obtain rewards. Complex action sequences were composed of simpler action sequences, which were not rewarded, but whose completion was signaled to participants. We investigated the process with which participants learned to perform simpler action sequences and combined them into complex action sequences. After learning action sequences, participants completed a transfer phase in which either simple sequences or complex sequences were manipulated without notice. Relearning progressed slower when simple than complex sequences were changed, in accordance with a hierarchical representations in which lower levels are quickly consolidated, potentially stabilizing exploration, while higher levels remain malleable, with benefits for flexible recombination.

摘要

人类具有惊人的能力,能够在没有外部奖励的情况下迅速适应不断变化的环境需求并实现复杂目标。这种能力的部分基础在于灵活复用和重新组合先前经验的能力,以及在由这些经验塑造的心理空间中规划未来行动方案的能力。数十年的研究表明,人类使用层次化表征进行高效规划和灵活应变,但这些表征的起源一直难以捉摸。本研究调查了73名参与者如何通过经验学习层次化表征,在一项任务中,他们必须执行复杂的动作序列以获得奖励。复杂动作序列由更简单的动作序列组成,这些简单动作序列没有奖励,但完成时会向参与者发出信号。我们研究了参与者学习执行更简单动作序列并将它们组合成复杂动作序列的过程。在学习动作序列后,参与者完成了一个迁移阶段,在此阶段中,简单序列或复杂序列会在未通知的情况下被操控。当简单序列而非复杂序列被改变时,重新学习的进展更慢,这与一种层次化表征一致,即较低层次会迅速巩固,可能稳定探索,而较高层次则保持可塑性,有利于灵活重组。

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