Farama-Foundation/Minigrid: papers linking to it

GitHub · 2,535 stars · 668 forks · Python · created 2017 · github.com/Farama-Foundation/Minigrid

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to Farama-Foundation/Minigrid (https://github.com/Farama-Foundation/Minigrid), 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.

Key findings#

6 papers in the tracked journals link to the GitHub repository Farama-Foundation/Minigrid in their Crossref records, the first in 2019; most of them (2) in 2025.
By category: AI (6); the journals with the most are Applied Intelligence (2), Neural Computing and Applications (2) and Neural Networks (1).
3 of the papers build on one another: a later paper cites an earlier one that also links Farama-Foundation/Minigrid.

By year#

20192025

Papers linking to Farama-Foundation/Minigrid by publication year
Year	Papers
2019	1
2020	1
2021	1
2022	1
2025	2

Journals#

Journals whose papers link to Farama-Foundation/Minigrid most
Journal	Papers
Applied Intelligence	2
Neural Computing and Applications	2
Neural Networks	1
Machine Learning	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Skill-based curiosity for intrinsically motivated reinforcement learning Machine Learning, 2019
- Fast and slow curiosity for high-level exploration in reinforcement learning Applied Intelligence, 2020 — cites the paper above
  - Hierarchical learning from human preferences and curiosity Applied Intelligence, 2021 — cites the paper above

Papers linking to Farama-Foundation/Minigrid, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-09-16	Fast and slow curiosity for high-level exploration in reinforcement learning	Applied Intelligence	Nicolas Bougie, Ryutaro Ichise	32	cites it
2019-10-10	Skill-based curiosity for intrinsically motivated reinforcement learning	Machine Learning	Nicolas Bougie, Ryutaro Ichise	31	cites it
2021-09-28	Hierarchical learning from human preferences and curiosity	Applied Intelligence	Nicolas Bougie, Ryutaro Ichise	10	cites it
2022-09-04	Influence-aware memory architectures for deep reinforcement learning in POMDPs	Neural Computing and Applications	Miguel Suau, Jinke He, Elena Congeduti et al.	5	cites it
2025-07-16	Representation-driven sampling and adaptive policy resetting for improving multi-Agent reinforcement learning	Neural Networks	Weiqiang Jin, Xingwu Tian, Ningwei Wang et al.	3	cites it
2025-04-12	Experiential Explanations for Reinforcement Learning	Neural Computing and Applications	Amal Alabdulkarim, Madhuri Singh, Gennie Mansi et al.	2	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). Farama-Foundation/Minigrid: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-farama-foundation-minigrid

@misc{scholar4ai-code-github-farama-foundation-minigrid,
  author = {{Scholar4AI}},
  title = {Farama-Foundation/Minigrid: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-farama-foundation-minigrid}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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