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Environment datasets
archive 2025-07-28147 datasets carry the modality tag "Environment", ordered by the archive's paper count. Page 1 of 4: 48 shown of 147. 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 39 modality tags shown of 39, by dataset count; the full filter by modality, task and language is on /datasets
All 12,172
Images 3,239Texts 3,130Videos 1,014Audio 480Medical 3943D 380Time series 294Graphs 282Tabular 267Speech 197RGB-D 190Environment 147Point cloud 134Biomedical 122LiDAR 94RGB Video 87Tracking 77Biology 70Actions 673d meshes 64Tables 50Music 47EEG 44Hyperspectral images 44Stereo 44MRI 39Physics 32Interactive 29Dialog 25Midi 226D 17Replay data 11Financial 10Ranking 10Cad 9fMRI 7Parallel 6Lyrics 2PSG 2
Environment datasets 1–48 of 147
MuJoCo (multi-joint dynamics with contact) is a physics engine used to implement environments to benchmark Reinforcement Learning methods.
1,638 papers · 2 benchmarks
CARLA (Car Learning to Act)
CARLA (CAR Learning to Act) is an open simulator for urban driving, developed as an open-source layer over Unreal Engine 4.
1,345 papers · 4 benchmarks
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms.
1,305 papers · 3 benchmarks
D4RL is a collection of environments for offline reinforcement learning.
538 papers · 2 benchmarks
The Arcade Learning Environment (ALE) is an object-oriented framework that allows researchers to develop AI agents for Atari 2600 games.
366 papers · 57 benchmarks
The DeepMind Control Suite (DMCS) is a set of simulated continuous control environments with a standardized structure and interpretable rewards.
364 papers · 3 benchmarks
AirSim is a simulator for drones, cars and more, built on Unreal Engine.
285 papers · 0 benchmarks
AI2-Thor is an interactive environment for embodied AI.
243 papers · 1 benchmark
Omniverse Isaac Gym is a GPU-based physics simulation platform developed by NVIDIA.
240 papers · 2 benchmarks
RLBench is an ambitious large-scale benchmark and learning environment designed to facilitate research in a number of vision-guided manipulation research areas, including: reinforcement learning, imitation learning, multi-task learning,…
167 papers · 2 benchmarks
ViZDoom is an AI research platform based on the classical First Person Shooter game Doom.
156 papers · 3 benchmarks
132 papers · 0 benchmarks
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators.
100 papers · 0 benchmarks
TORCS (The Open Racing Car Simulator)
TORCS (The Open Racing Car Simulator) is a driving simulator.
96 papers · 0 benchmarks
Kubric is a data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
77 papers · 1 benchmark
Jericho is a learning environment for man-made Interactive Fiction (IF) games.
54 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
ManiSkill is a large-scale learning-from-demonstrations benchmark for articulated object manipulation with visual input (point cloud and image).
38 papers · 0 benchmarks
GVGAI (General Video Game AI)
The General Video Game AI (GVGAI) framework is widely used in research which features a corpus of over 100 single-player games and 60 two-player games.
36 papers · 0 benchmarks
TEACh (Task-driven Embodied Agents that Chat)
Robots operating in human spaces must be able to engage in natural language interaction with people, both understanding and executing instructions, and using conversation to resolve ambiguity and recover from mistakes.
36 papers · 0 benchmarks
PHYRE (PHYsical REasoning)
Benchmark for physical reasoning that contains a set of simple classical mechanics puzzles in a 2D physical environment.
35 papers · 2 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
The StarCraft II Learning Environment (S2LE) is a reinforcement learning environment based on the game StarCraft II.
26 papers · 0 benchmarks
The NetHack Learning Environment (NLE) is a Reinforcement Learning environment based on NetHack 3.6.6.
23 papers · 1 benchmark
Gibson is an opensource perceptual and physics simulator to explore active and real-world perception.
22 papers · 0 benchmarks
MINOS is a simulator designed to support the development of multisensory models for goal-directed navigation in complex indoor environments.
22 papers · 0 benchmarks
Obstacle Tower is a high fidelity, 3D, 3rd person, procedurally generated environment for reinforcement learning.
20 papers · 6 benchmarks
Physion is a visual and physical prediction benchmark to measure the performance of machine learning models on making predictions about commonplace real world physical events.
19 papers · 0 benchmarks
Bridge Data is a large multi-domain and multi-task dataset, with 7,200 demonstrations constituting 71 tasks across 10 environments.
18 papers · 0 benchmarks
PasticineLab is a differentiable physics benchmark, which includes a diverse collection of soft body manipulation tasks.
16 papers · 0 benchmarks
RTMV is a large-scale synthetic dataset for novel view synthesis consisting of ∼300k images rendered from nearly 2000 complex scenes using high-quality ray tracing at high resolution (1600 × 1600 pixels).
15 papers · 1 benchmark
SUMMIT is a high-fidelity simulator that facilitates the development and testing of crowd-driving algorithms.
14 papers · 0 benchmarks
RGB-Stacking is a benchmark for vision-based robotic manipulation.
13 papers · 3 benchmarks
LANI is a 3D navigation environment and corpus, where an agent navigates between landmarks.
12 papers · 0 benchmarks
12 papers · 0 benchmarks
A rich, extensible and efficient environment that contains 45,622 human-designed 3D scenes of visually realistic houses, ranging from single-room studios to multi-storied houses, equipped with a diverse set of fully labeled 3D objects,…
11 papers · 0 benchmarks
Mario AI was a benchmark environment for reinforcement learning.
11 papers · 0 benchmarks
SMAC-Exp (StarCraft Multi-Agent Exploration Challenge)
The StarCraft Multi-Agent Challenges+ requires agents to learn completion of multi-stage tasks and usage of environmental factors without precise reward functions.
11 papers · 2 benchmarks
CHALET (Cornell House Agent Learning Environment)
CHALET is a 3D house simulator with support for navigation and manipulation.
10 papers · 0 benchmarks
10 papers · 0 benchmarks
Memory Maze is a 3D domain of randomized mazes designed for evaluating the long-term memory abilities of RL agents.
10 papers · 0 benchmarks
- NeoRL is a collection of environments and datasets for offline reinforcement learning with a special focus on real-world applications.
10 papers · 0 benchmarks
RoomR (Room Rearrangement)
The task of Room Rearrangement consists on an agent exploring a room and recording objects' initial configurations.
10 papers · 0 benchmarks
iGibson 2.0 is an open-source simulation environment that supports the simulation of a more diverse set of household tasks through three key innovations.
10 papers · 0 benchmarks
Our dataset which consists of multiple indoor and outdoor experiments for up to 30 m gNB-UE link.
9 papers · 0 benchmarks
MO-Gymnasium is an open source Python library for developing and comparing multi-objective reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set…
8 papers · 0 benchmarks
Spider 2.0 is a comprehensive code generation agent task that includes 632 examples.
8 papers · 1 benchmark
WADS (Winter Adverse Driving dataSet)
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather.
8 papers · 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.