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Reinforcement Learning (RL) datasets

archive 2025-07-28

20 datasets carry the task tag "Reinforcement Learning (RL)" (the task itself: Reinforcement Learning (RL)), ordered by the archive's paper count. Page 1 of 1: 20 shown of 20. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Reinforcement Learning (RL) datasets 1–20 of 20

Procgen Benchmark includes 16 simple-to-use procedurally-generated environments which provide a direct measure of how quickly a reinforcement learning agent learns generalizable skills.
177 papers · 1 benchmark
PRM800K is a process supervision dataset containing 800,000 step-level correctness labels for model-generated solutions to problems from the MATH dataset.
53 papers · 0 benchmarks
ManiSkill2 is the next generation of the SAPIEN ManiSkill benchmark, to address critical pain points often encountered by researchers when using benchmarks for generalizable manipulation skills.
40 papers · 0 benchmarks
SMACv2 (StarCraft Multi-Agent Challenge v2) is a new version of the benchmark where scenarios are procedurally generated and require agents to generalise to previously unseen settings (from the same distribution) during evaluation.
30 papers · 0 benchmarks
V-D4RL provides pixel-based analogues of the popular D4RL benchmarking tasks, derived from the dmcontrol suite, along with natural extensions of two state-of-the-art online pixel-based continuous control algorithms, DrQ-v2 and DreamerV2,…
16 papers · 0 benchmarks
This is a gun detection dataset with 51K annotated gun images for gun detection and other 51K cropped gun chip images for gun classification collected from a few different sources.
9 papers · 6 benchmarks
QDax is a benchmark suite designed for for Deep Neuroevolution in Reinforcement Learning domains for robot control.
6 papers · 0 benchmarks
Avalon is a benchmark for generalization in Reinforcement Learning (RL).
5 papers · 0 benchmarks
FinRL-Meta is universe of market environments for data-driven financial reinforcement learning.
5 papers · 0 benchmarks
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
4 papers · 0 benchmarks
POPGym (Partially Observable Process Gym)
POPGym is designed to benchmark memory in deep reinforcement learning.
3 papers · 0 benchmarks
MIDGARD is an open-source simulator for autonomous robot navigation in outdoor unstructured environments.
2 papers · 0 benchmarks
first everyday task dataset featuring COT outputs, diverse task designs, detailed re-plan processes, along with SFT and DPO sub-datasets.
1 paper · 0 benchmarks
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
1 paper · 0 benchmarks
The dataset comprises 1641 questions and answers generated as three separate parts.
1 paper · 0 benchmarks
PushWorld is an environment with simplistic physics that requires manipulation planning with both movable obstacles and tools.
1 paper · 0 benchmarks
RoomEnv-v1 (The Room environment - v1)
The Room environment - v1 We have released a challenging Gymnasium compatible environment.
1 paper · 1 benchmark
RoomEnv-v2 (The Room environment - v2)
The Room environment - v2 We have released a challenging Gymnasium compatible environment.
1 paper · 1 benchmark
lilGym is a benchmark for language-conditioned reinforcement learning in visual environment based on 2,661 highly-compositional human-written natural language statements grounded in an interactive visual environment.
1 paper · 0 benchmarks
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.