mlsanityData to 14 Oct 2026

dm_control: Software and Tasks for Continuous Control

arXiv 2006.12983 ↗First posted 22 Jun 2020cs.RO cs.AI cs.LGcited by 375

Not on the map. Why?

Cited by 121 in Deep reinforcement learning methods, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A MuJoCo wrapper provides convenient bindings to functions and data structures. The PyMJCF and Composer libraries enable procedural model manipulation and task authoring. The Control Suite is a fixed set of tasks with standardised structure, intended to serve as performance benchmarks. The Locomotion framework provides high-level abstractions and examples of locomotion tasks. A set of configurable manipulation tasks with a robot arm and snap-together bricks is also included. dm_control is publicly available at https://www.github.com/deepmind/dm_control

Key facts. Cited by 375 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Jun 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2020: 4; 2021: 43; 2022: 61; 2023: 73; 2024: 80; 2025: 60; 2026: 54.

375 papers.

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  1. 2022A Generalist Agentcited by 808
  2. 2023Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Taskscited by 327
  3. 2021PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-trainingcited by 302
  4. 2022The Primacy Bias in Deep Reinforcement Learningcited by 247
  5. 2022A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problemscited by 231
  6. 2024ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AIcited by 229
  7. 2021ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrationscited by 197
  8. 2024VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Taskscited by 175
  9. 2021Behavior From the Void: Unsupervised Active Pre-Trainingcited by 174
  10. 2023RoCo: Dialectic Multi-Robot Collaboration with Large Language Modelscited by 172
  11. 2022Masked World Models for Visual Controlcited by 170
  12. 2021Embodied Intelligence via Learning and Evolutioncited by 163
38 more
  1. 2022Goal-Conditioned Reinforcement Learning: Problems and Solutionscited by 158
  2. 2023Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmarkcited by 143
  3. 2023Vision-Language Models as Success Detectorscited by 142
  4. 2023Learning a Diffusion Model Policy from Rewards via Q-Score Matchingcited by 138
  5. 2023Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learningcited by 133
  6. 2023SmartPlay: A Benchmark for LLMs as Intelligent Agentscited by 125
  7. 2021Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learningcited by 123
  8. 2020Hyperparameter Selection for Offline Reinforcement Learningcited by 114
  9. 2024HumanoidBench: Simulated Humanoid Benchmark for Whole-Body Locomotion and Manipulationcited by 112
  10. 2021State Entropy Maximization with Random Encoders for Efficient Explorationcited by 108
  11. 2022Reinforcement Learning with Action-Free Pre-Training from Videoscited by 108
  12. 2021B-Pref: Benchmarking Preference-Based Reinforcement Learningcited by 106
  13. 2023Synthetic Experience Replaycited by 101
  14. 2025Flow Matching Policy Gradientscited by 99
  15. 2022SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learningcited by 97
  16. 2020Offline Reinforcement Learning from Images with Latent Space Modelscited by 95
  17. 2022Instruction-driven history-aware policies for robotic manipulationscited by 94
  18. 2021From Motor Control to Team Play in Simulated Humanoid Footballcited by 87
  19. 2022Few-Shot Preference Learning for Human-in-the-Loop RLcited by 87
  20. 2022A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learningcited by 83
  21. 2021VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehiclescited by 81
  22. 2023Video Prediction Models as Rewards for Reinforcement Learningcited by 78
  23. 2021Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Controlcited by 77
  24. 2021Learning and Planning in Complex Action Spacescited by 77
  25. 2024Real2Code: Reconstruct Articulated Objects via Code Generationcited by 69
  26. 2022Denoised MDPs: Learning World Models Better Than the World Itselfcited by 68
  27. 2023Vision-Language Models as a Source of Rewardscited by 66
  28. 2022Challenges and Opportunities in Offline Reinforcement Learning from Visual Observationscited by 63
  29. 2022EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Enginecited by 62
  30. 2022Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learningcited by 60
  31. 2023TorchRL: A data-driven decision-making library for PyTorchcited by 60
  32. 2025DIME:Diffusion-Based Maximum Entropy Reinforcement Learningcited by 58
  33. 2020RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learningcited by 57
  34. 2025Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Modelscited by 56
  35. 2022skrl: Modular and Flexible Library for Reinforcement Learningcited by 49
  36. 2021Vector Quantized Models for Planningcited by 48
  37. 2024Gymnasium: A Standard Interface for Reinforcement Learning Environmentscited by 46
  38. 2021Learning Markov State Abstractions for Deep Reinforcement Learningcited by 44

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