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ChainerRL: A Deep Reinforcement Learning Library

arXiv 1912.03905 ↗First posted 9 Dec 2019cs.LG cs.AI stat.MLcited by 51

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Abstract (arXiv)

In this paper, we introduce ChainerRL, an open-source deep reinforcement learning (DRL) library built using Python and the Chainer deep learning framework. ChainerRL implements a comprehensive set of DRL algorithms and techniques drawn from state-of-the-art research in the field. To foster reproducible research, and for instructional purposes, ChainerRL provides scripts that closely replicate the original papers' experimental settings and reproduce published benchmark results for several algorithms. Lastly, ChainerRL offers a visualization tool that enables the qualitative inspection of trained agents. The ChainerRL source code can be found on GitHub: https://github.com/chainer/chainerrl.

Key facts. Cited by 51 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Dec 2019.

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Citing papers per year: 2021: 15; 2022: 13; 2023: 7; 2024: 8; 2025: 7; 2026: 1.

51 papers.

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  1. 2021Tianshou: a Highly Modularized Deep Reinforcement Learning Librarycited by 143
  2. 2022CORL: Research-oriented Deep Offline Reinforcement Learning Librarycited by 119
  3. 2021d3rlpy: An Offline Deep Reinforcement Learning Librarycited by 84
  4. 2021GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Drivingcited by 60
  5. 2023TorchRL: A data-driven decision-making library for PyTorchcited by 60
  6. 2022skrl: Modular and Flexible Library for Reinforcement Learningcited by 49
  7. 2021The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priorscited by 41
  8. 2024BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidencecited by 28
  9. 2022Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performancecited by 22
  10. 2021Recurrent Off-policy Baselines for Memory-based Continuous Controlcited by 21
  11. 2021Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimizationcited by 18
  12. 2022Topological Experience Replaycited by 17
38 more
  1. 2024Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learningcited by 17
  2. 2022A2C is a special case of PPOcited by 16
  3. 2021Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learningcited by 15
  4. 2021PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systemscited by 14
  5. 2021Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximizationcited by 11
  6. 2023Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networkscited by 11
  7. 2024Investigating the Histogram Loss in Regressioncited by 11
  8. 2024Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Surveycited by 8
  9. 2021A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systemscited by 5
  10. 2021ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectivescited by 5
  11. 2023XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Librarycited by 5
  12. 2024Dataset Distillation for Offline Reinforcement Learningcited by 5
  13. 2022RLSS: A Deep Reinforcement Learning Algorithm for Sequential Scene Generationcited by 4
  14. 2022RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agentscited by 4
  15. 2023RLtools: A Fast, Portable Deep Reinforcement Learning Library for Continuous Controlcited by 4
  16. 2021CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithmscited by 3
  17. 2023RLLTE: Long-Term Evolution Project of Reinforcement Learningcited by 3
  18. 2024Evaluation of Reinforcement Learning for Autonomous Penetration Testing using A3C, Q-learning and DQNcited by 3
  19. 2021Did I do that? Blame as a means to identify controlled effects in reinforcement learningcited by 2
  20. 2021Parallel Actors and Learners: A Framework for Generating Scalable RL Implementationscited by 2
  21. 2022ExPoSe: Combining State-Based Exploration with Gradient-Based Online Searchcited by 2
  22. 2025The Cell Must Go On: Agar.io for Continual Reinforcement Learningcited by 2
  23. 2025An Analysis of Action-Value Temporal-Difference Methods That Learn State Valuescited by 2
  24. 2022Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environmentscited by 1
  25. 2022tinyMAN: Lightweight Energy Manager using Reinforcement Learning for Energy Harvesting Wearable IoT Devicescited by 1
  26. 2023Diverse Policy Optimization for Structured Action Spacecited by 1
  27. 2024Stimulate the Potential of Robots via Competitioncited by 1
  28. 2024AgGym: An agricultural biotic stress simulation environment for ultra-precision management planningcited by 1
  29. 2025Together We Rise: Optimizing Real-Time Multi-Robot Task Allocation using Coordinated Heterogeneous Playscited by 1
  30. 2025Experience Replay with Random Reshufflingcited by 1
  31. 2025Deep Double Q-learningcited by 1
  32. 2021The AI Arena: A Framework for Distributed Multi-Agent Reinforcement Learningcited by 0
  33. 2022JORLDY: a fully customizable open source framework for reinforcement learningcited by 0
  34. 2022Dynamically writing coupled memories using a reinforcement learning agent, meeting physical boundscited by 0
  35. 2022SHIRO: Soft Hierarchical Reinforcement Learningcited by 0
  36. 2023EduGym: An Environment and Notebook Suite for Reinforcement Learning Educationcited by 0
  37. 2025Enhancing Offline Reinforcement Learning with Curriculum Learning-Based Trajectory Valuationcited by 0
  38. 2025CiRL: Open-Source Environments for Reinforcement Learning in Circular Economy and Net Zerocited by 0

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