The real world is stochastic, making it difficult to know when planning is worthwhile. Here the authors show that as stochasticity increases, people spend less effort planning and adopt simpler, less ...

The nativist–empiricist debate has long organized cognitive science, framing cognitive mechanisms as either innate or learned. Recent advances in controlled rearing and scalable domain-general neural ...

Most widely studied option evaluation strategies rely on knowledge accumulated across repeated experiences. But how should options be evaluated in ...

MIT researchers study human cognition through logic puzzles

Flexible decision making depends on retrieving and recombining memories. Yet because this process unfolds covertly, its governing principles remain unknown. Here we use gaze reinstatement to uncover t...

A workshop series on representation construction in cognitive science and AI. CogSci 2026 (Rio) and CCN 2026 (NYU).

When do machine learning systems fail to generalize, and what mechanisms could improve their generalization? Here, we draw inspiration from cognitive science to argue that one weakness of...

Nature Human Behaviour, Published online: 05 February 2026; doi:10.1038/s41562-025-02324-0Using artificial neural networks applied to human data, Eckstein et al. show that good models of reinforcement learning require memory components that track representations of the past.