Unknown

Dataset Information

Humans monitor learning progress in curiosity-driven exploration.


ABSTRACT: Curiosity-driven learning is foundational to human cognition. By enabling humans to autonomously decide when and what to learn, curiosity has been argued to be crucial for self-organizing temporally extended learning curricula. However, the mechanisms driving people to set intrinsic goals, when they are free to explore multiple learning activities, are still poorly understood. Computational theories propose different heuristics, including competence measures (e.g., percent correct) and learning progress, that could be used as intrinsic utility functions to efficiently organize exploration. Such intrinsic utilities constitute computationally cheap but smart heuristics to prevent people from laboring in vain on unlearnable activities, while still motivating them to self-challenge on difficul

SUBMITTER: Ten A 

PROVIDER: S-EPMC8514490 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature