mlsanityData to 14 Oct 2026

Godot Reinforcement Learning Agents

arXiv 2112.03636 ↗First posted 7 Dec 2021cs.LGcited by 4

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Abstract (arXiv)

We present Godot Reinforcement Learning (RL) Agents, an open-source interface for developing environments and agents in the Godot Game Engine. The Godot RL Agents interface allows the design, creation and learning of agent behaviors in challenging 2D and 3D environments with various on-policy and off-policy Deep RL algorithms. We provide a standard Gym interface, with wrappers for learning in the Ray RLlib and Stable Baselines RL frameworks. This allows users access to over 20 state of the art on-policy, off-policy and multi-agent RL algorithms. The framework is a versatile tool that allows researchers and game designers the ability to create environments with discrete, continuous and mixed action spaces. The interface is relatively performant, with 12k interactions per second on a high end laptop computer, when parallized on 4 CPU cores. An overview video is available here: https://youtu.be/g1MlZSFqIj4

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 40 of its 58 references that are in the map. First posted on arXiv 7 Dec 2021.

Builds on

40 of 58 references.

References · 40

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  3. 2015Continuous control with deep reinforcement learningcited by 3,407
  4. 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
  5. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,258
  6. 2020Conservative Q-Learning for Offline Reinforcement Learningcited by 1,809
  7. 2016OpenAI Gymcited by 1,736
  8. 2017Curiosity-driven Exploration by Self-supervised Predictioncited by 1,194
  9. 2019Habitat: A Platform for Embodied AI Researchcited by 1,191
  10. 2018IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architecturescited by 883
  11. 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 869
  12. 2017Rainbow: Combining Improvements in Deep Reinforcement Learningcited by 786
28 more
  1. 2017Evolution Strategies as a Scalable Alternative to Reinforcement Learningcited by 574
  2. 2021Habitat 2.0: Training Home Assistants to Rearrange their Habitatcited by 511
  3. 2018Gibson Env: Real-World Perception for Embodied Agentscited by 481
  4. 2020Object Goal Navigation using Goal-Oriented Semantic Explorationcited by 429
  5. 2016Reinforcement Learning with Unsupervised Auxiliary Taskscited by 404
  6. 2016Learning to reinforcement learncited by 377
  7. 2019DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Framescited by 362
  8. 2020Learning to Explore using Active Neural SLAMcited by 316
  9. 2018Distributed Prioritized Experience Replaycited by 269
  10. 2018Unity: A General Platform for Intelligent Agentscited by 236
  11. 2016Learning to Navigate in Complex Environmentscited by 198
  12. 2020Neural Topological SLAM for Visual Navigationcited by 195
  13. 2019OpenSpiel: A Framework for Reinforcement Learning in Gamescited by 186
  14. 2019Soft Actor-Critic for Discrete Action Settingscited by 174
  15. 2020Acme: A Research Framework for Distributed Reinforcement Learningcited by 146
  16. 2016Playing FPS Games with Deep Reinforcement Learningcited by 95
  17. 2020Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learningcited by 93
  18. 2016DeepMind Labcited by 74
  19. 2018Unsupervised Predictive Memory in a Goal-Directed Agentcited by 55
  20. 2015Gated Feedback Recurrent Neural Networkscited by 54
  21. 2018ViZDoom Competitions: Playing Doom from Pixelscited by 51
  22. 2020Semantic Curiosity for Active Visual Learningcited by 45
  23. 2018Accelerated Methods for Deep Reinforcement Learningcited by 40
  24. 2021Adversarial Reinforcement Learning for Procedural Content Generationcited by 36
  25. 2020Learning to plan with uncertain topological mapscited by 29
  26. 2021Improving Playtesting Coverage via Curiosity Driven Reinforcement Learning Agentscited by 28
  27. 2020Deep Reinforcement Learning for Navigation in AAA Video Gamescited by 27
  28. 2020EgoMap: Projective mapping and structured egocentric memory for Deep RLcited by 23

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 1.

4 papers.

  1. 2023Games for Artificial Intelligence Research: A Review and Perspectivescited by 14
  2. 2024A Review of Nine Physics Engines for Reinforcement Learning Researchcited by 12
  3. 2023Improving Intrinsic Exploration by Creating Stationary Objectivescited by 7
  4. 2026CA2: Code-Aware Agent for Automated Game Testingcited by 0