# Farama-Foundation/Minigrid

Simple and easily configurable grid world environments for reinforcement learning

Repository: https://github.com/Farama-Foundation/Minigrid
Canonical: https://ross.abutalabs.com/products/minigrid
Homepage: https://minigrid.farama.org/
Language: Python
License: NOASSERTION
License Family: other
Topics: gridworld-environment, gymnasium, gymnasium-environment
Last push: 2026-08-24T22:06:07+00:00

## Health v2 (maintenance only)
Score: 82/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 51, longevity 100
- inputs: {"age_days": 3185, "days_push": 9, "days_rel": 114, "gap_med": 539, "n_releases_24m": 2}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2499, forks 647 (observed 2026-08-28T04:06:56.869450+00:00)

## What it is
Minigrid is a Python library of lightweight, easily configurable discrete grid-world environments for reinforcement learning research, following the Gymnasium API. It includes the original Minigrid environments plus BabyAI and WFC-generated environment suites with customizable wrappers and observation spaces.

## Use cases
- train RL agents on gridworld navigation tasks
- benchmark reinforcement learning algorithms on simple environments
- create custom gridworld environments for RL research
- test hierarchical instruction-following agents with BabyAI tasks
- generate procedural mazes and dungeons with WFC environments
- prototype RL experiments without heavy simulation overhead

## When to choose
- you need fast, lightweight RL environments with the Gymnasium API
- you want easily customizable gridworld tasks for research
- you need hierarchical or instruction-based missions like BabyAI
- you want a well-established benchmark cited in many publications

## When to avoid
- you need photorealistic or 3D simulation environments
- you require official Windows support
- you need continuous control or robotics-style environments

## Facets
- artifact type: library
- maturity: active
- function: simulation, machine-learning, reinforcement-learning
- domain: reinforcement-learning, machine-learning, simulation
- platform: python
- tags: gridworld, gymnasium, environments, babyai, rl-benchmarks, research, linux, macos

## Member repositories
- Farama-Foundation/Minigrid (main) score 82

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:56.869450+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:26:57.700855+00:00, confidence not recorded.
  - readme: https://github.com/Farama-Foundation/Minigrid (fetched 2026-08-28T04:06:56.869450+00:00, sha b45393d9b106)
  - homepage: https://minigrid.farama.org/ (fetched 2026-08-29T10:09:26.072164+00:00, sha 1c67ec889c0a)
  - registry_pypi: https://pypi.org/pypi/minigrid/json (fetched 2026-08-29T10:09:26.084061+00:00, sha 7e6b0d4c57dc)
  - site_page: https://minigrid.farama.org/content/basic_usage (fetched 2026-08-29T10:09:26.081772+00:00, sha f12e8cf385f7)
- Data as of 2026-08-30T08:39:29.467469+00:00.