---
title: "Computational Theories of Curiosity-Driven Learning"
description: "3 papers in the tracked journals link to the OSF dataset Computational Theories of Curiosity-Driven Learning in their Crossref records, the first in 2022; most of them (2) in 2022."
url: https://scholar4ai.com/code/osf-3p8f6
markdown_url: https://scholar4ai.com/code/osf-3p8f6.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the OSF dataset Computational Theories of Curiosity-Driven Learning in their Crossref records, the first in 2022; most of them (2) in 2022. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# Computational Theories of Curiosity-Driven Learning: papers linking to it

Research papers in the 480 tracked journals that link to Computational Theories of Curiosity-Driven Learning (https://osf.io/3p8f6/), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- OSF
- Text
- 2018
- https://osf.io/3p8f6/

All repositories: https://scholar4ai.com/code.md

## Key findings

- 3 papers in the tracked journals link to the OSF dataset Computational Theories of Curiosity-Driven Learning in their Crossref records, the first in 2022; most of them (2) in 2022.
- By category: AI (3); the journals with the most are Nature Machine Intelligence (2) and Cognitive Computation (1).

## By year

*Papers linking to Computational Theories of Curiosity-Driven Learning by publication year*

| Year | Papers |
|---|---:|
| 2022 | 2 |
| 2023 | 1 |

## Journals

*Journals whose papers link to Computational Theories of Curiosity-Driven Learning most*

| Journal | Papers |
|---|---:|
| [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2 |
| [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 1 |

## Papers

*Papers linking to Computational Theories of Curiosity-Driven Learning, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-01-25 | [Intelligent problem-solving as integrated hierarchical reinforcement learning](https://doi.org/10.1038/s42256-021-00433-9) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Manfred Eppe, Christian Gumbsch, Matthias Kerzel et al. | 99 | cites it |
| 2022-06-22 | [Lessons from infant learning for unsupervised machine learning](https://doi.org/10.1038/s42256-022-00488-2) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Lorijn Zaadnoordijk, Tarek R. Besold, Rhodri Cusack | 66 | cites it |
| 2023-10-28 | [Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning](https://doi.org/10.1007/s12559-023-10213-9) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Pankayaraj Pathmanathan, Natalia Díaz-Rodríguez, Javier Del Ser | 1 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). Computational Theories of Curiosity-Driven Learning: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/osf-3p8f6

```bibtex
@misc{scholar4ai-code-osf-3p8f6,
  author = {{Scholar4AI}},
  title = {Computational Theories of Curiosity-Driven Learning: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/osf-3p8f6}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).