Evidence map›Paper›PMID 42459224›Full record

ArticleComputational brain & behavior2025

The Effect of Reward Magnitude on Different Types of Exploration in Human Reinforcement Learning.

Kanji Shimomura, Kenji Morita

Abstract read
In one paragraph

Article in Computational brain & behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Kanji ShimomuraGraduate School of Education, The University of Tokyo, Tokyo, Japan.
Kenji MoritaGraduate School of Education, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

How humans resolve the explore-exploit dilemma in complex environments is an important open question. Previous studies suggested that environmental richness may affect the degree of exploration in a type-specific manner and reduce random exploration while increasing uncertainty-based exploration. Our study examined this possibility by extending a recently developed two-armed bandit task that can dissociate the uncertainty and novelty of stimuli. To extract the pure effect of environmental richness, we manipulated the reward by its magnitude, not its probability, across blocks because reward probability affects outcome controllability. Participants ( Supplementary Information: The online version contains supplementary material available at 10.1007/s42113-024-00224-6.

Indexed as

Directed explorationExplore-exploit tradeoffRandom explorationReinforcement learningReward magnitude

Identifiers

PMID42459224
PMCPMC13298669

What OpenQuestion holds

Textmetadata
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.