ArticleNature communications2021
Humans monitor learning progress in curiosity-driven exploration.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed, 84 citations in OpenAlex.
- Learning reinforces curiosity for related information.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- More Time and Effort, Same Curiosity: Expected Effort Does Not Impact Curiosity.Open mind : discoveries in cognitive science · 2026Article
- Individual Differences in Infants' Curiosity Are Linked to Cognitive Capacity in Early Childhood.Developmental science · 2026Article
- No Evidence for Curiosity-Driven Information Selection Advantage in Infants' Novel Word Learning.Developmental science · 2026Article
- Learning expectations shape cognitive control allocation.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Leveling up fun: learning progress, expectations, and success influence enjoyment in video games.Scientific reports · 2025Article
- Novelty as a drive of human exploration in complex stochastic environments.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Single-Neuron Encoding of Learnability in the Dorsal Anterior Cingulate Cortex.bioRxiv : the preprint server for biology · 2025Article
- The Neural Markers of Perceptual Uncertainty/Curiosity-A Functional Near-Infrared Spectroscopy Pilot Study.Brain sciences · 2025Article
- To know or not to know? Curiosity and the value of prospective information in animals.Learning & behavior · 2025Review
- The CuriousOpen mind : discoveries in cognitive science · 2025Article
- Curiosity shapes spatial exploration and cognitive map formation in humans.Communications psychology · 2024Article
- Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning.Advances in neural information processing systems · 2024Article
- Individual differences in information demand have a low dimensional structure predicted by some curiosity traits.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Autistic traits foster effective curiosity-driven exploration.PLoS computational biology · 2024Article
- Curiosity: primate neural circuits for novelty and information seeking.Nature reviews. Neuroscience · 2024Review
- Interactive curriculum learning increases and homogenizes motor smoothness.Scientific reports · 2024Article
- Pushing the Bounds of Bounded Optimality and Rationality.Cognitive science · 2023Article
- Article
- Motivated for near impossibility: How task type and reward modulate task enjoyment and the striatal activation for extremely difficult task.Cognitive, affective & behavioral neuroscience · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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 difficult learnable activities. Here, we provide empirical evidence for these ideas by means of a free-choice experimental paradigm and computational modeling. We show that while humans rely on competence information to avoid easy tasks, models that include a learning-progress component provide the best fit to task selection data. These results bridge the research in artificial and biological curiosity, reveal strategies that are used by humans but have not been considered in computational research, and introduce tools for probing how humans become intrinsically motivated to learn and acquire interests and skills on extended time scales.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.