Category

Geospatial: RL environments and AI benchmarks

AI benchmarks
14
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Snapshot 2026-10-11. How categories are built · Where the data comes from

In short

What are RL environments for geospatial?
A simulated workplace where an AI agent practises a task (a code repository, a browser, business software) and an automatic grader scores each attempt. Labs train on thousands of these attempts. Bought to improve models.

Only benchmarks use the Geospatial tag: the RL environment directories file their vendors under other categories. Browse all RL environments.

AI benchmarks 14

None confirmed yet.

14 not yet confirmedListed in the catalog; no line from its own site or paper confirms it yet.
  1. CHOICE
  2. SustainBench
  3. GeoCode Leaderboard
  4. EO-Gym
  5. Urban-ImageNet
  6. OpenEarthMap
  7. GeoRC
  8. OmniEarth-Bench
  9. CITYREP
  10. htkgh-polecat
  11. POLECAT-FOR-ME
  12. SQuID
  13. Do Open-Vocabulary Detectors Transfer to Aerial Imagery? A Comparative Evaluation
  14. Urban Socio-Semantic Segmentation with Vision-Language Reasoning

Next: pick another domain. Tags come from the RL Research daily scrape, canonicalized nightly.