Extracting the structure of complex environments is at the core of our ability to interpret the present and predict the future. This skill is important for a range of behaviours from navigating a new city to learning music and language. Classical approaches that investigate our ability to extract the principles of organisation that govern complex environments focus on reward-based learning. Yet, the human brain is shown to be expert at learning generative structure based on mere exposure and without explicit reward. Individuals are shown to adapt to-unbeknownst to them-changes in the environment's temporal statistics and predict future events. Further, we present evidence for a common brain architecture for unsupervised structure learning and reward-based learning, suggesting that the brain is built on the premise that 'learning is its own reward' to support adaptive behaviour.

中文翻译：

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在没有老师的情况下学习预测结构：决策策略和大脑路线。

提取复杂环境的结构是我们解释现在和预测未来能力的核心。这项技能对于从导航新城市到学习音乐和语言的一系列行为都很重要。研究我们提取管理复杂环境的组织原则的能力的经典方法侧重于基于奖励的学习。然而，人类大脑被证明是学习生成结构的专家，仅基于暴露而没有明确的奖励。个体被证明能够适应环境时间统计数据的变化——他们不知道——并预测未来的事件。此外，我们提供了用于无监督结构学习和基于奖励的学习的通用大脑架构的证据，表明大脑是建立在以下前提之上的：