Humans adaptively select different computational strategies in different learning environments.
Pieter Verbeke, Tom Verguts · Psychological Review · 2024
= 407) divided over three reinforcement learning environments. Our results demonstrate that different environments are best solved with different learning strategies; and that humans adaptively select the learning strategy that allows best performance. Specifically, while flat learning fitted best in less complex stable learning environments, humans employed more hierarchically complex models in more complex environments. (PsycInfo Database Record (c) 2025 APA, all rights reserved).