Evidence map›Paper›PMID 35421742›Full record

ArticleCognition2022

Contributions of expected learning progress and perceptual novelty to curiosity-driven exploration.

Francesco Poli, Marlene Meyer, Rogier B Mars, Sabine Hunnius

Abstract read
In one paragraph

Article in Cognition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Novelty as a drive of human exploration in complex stochastic environments.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Article
  10. Article
  11. The CuriousOpen mind : discoveries in cognitive science · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. The aesthetic valve: how aesthetic appreciation may switch emotional states from anxiety to curiosity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  16. Article
  17. Article
  18. Eight-Month-Old Infants Meta-Learn by Downweighting Irrelevant Evidence.Open mind : discoveries in cognitive science · 2023
    Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Francesco PoliDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands. Electronic address: f.poli@psych.ru.nl.
Marlene MeyerDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.
Rogier B MarsDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
Sabine HunniusDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.

Funding

Biotechnology and Biological Sciences Research Council BB/N019814/1Wellcome TrustWellcome Trust 203139/Z/16/Z
6 · The paper itself

Abstract

Exploration is curiosity-driven when it relies on the intrinsic motivation to know rather than on extrinsic rewards. Recent evidence shows that artificial agents perform better on a variety of tasks when their learning is curiosity-driven, and humans often engage in curiosity-driven learning when sampling information from the environment. However, which mechanisms underlie curiosity is still unclear. Here, we let participants freely explore different unknown environments that contained learnable sequences of events with varying degrees of noise and volatility. A hierarchical reinforcement learning model captured how participants were learning in these different kinds of unknown environments, and it also tracked the errors they expected to make and the learning opportunities they were planning to seek. With this computational approach, we show that participants' exploratory behavior is guided by learning progress and perceptual novelty. Moreover, we demonstrate an overall tendency of participants to avoid extreme forms of uncertainty. These findings elucidate the cognitive mechanisms that underlie curiosity-driven exploration of unknown environments. Implications of this novel way of quantifying curiosity within a reinforcement learning framework are discussed.

Indexed as

Exploratory BehaviorLearningHumansMotivationReinforcement, PsychologyRewardComputational modelingCuriosityExplorationLearning progressNoveltyUncertainty

Identifiers

PMID35421742
PMCPMC9194910

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.