---
title: "Who cites Minigrid & Miniworld: Modular & — 21 citing papers"
description: "21 papers of the Elamur Research library cite «Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for…"
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---
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# Who cites «Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks»

21 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks»](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2023-minigrid-miniworld-modular-customizable-reinforcement/)

1. [**Gymnasium: A Standard Interface for Reinforcement Learning Environments arXiv:2407.17032**Mark Towers, Ariel Kwiatkowski, Jordan Terry, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/towers-2024-gymnasium-standard-interface-reinforcement-learning/)
2. **[DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents](https://md.research.elamur.ai/free/en/papers/jansen-2024-discoveryworld-virtual-environment-developing/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Peter Jansen, Marc-Alexandre Côté, Tushar Khot, et al.*2024 · 43 citations*
3. **[WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment](https://md.research.elamur.ai/free/en/papers/tang-2024-worldcoder-model-based-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hao Tang, Darren Key, Kevin Ellis*2024 · 32 citations*

18 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2023-minigrid-miniworld-modular-customizable-reinforcement/) — Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks