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Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU

arXiv 1611.06256 ↗First posted 18 Nov 2016cs.LGcited by 48

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Abstract (arXiv)

We introduce a hybrid CPU/GPU version of the Asynchronous Advantage Actor-Critic (A3C) algorithm, currently the state-of-the-art method in reinforcement learning for various gaming tasks. We analyze its computational traits and concentrate on aspects critical to leveraging the GPU's computational power. We introduce a system of queues and a dynamic scheduling strategy, potentially helpful for other asynchronous algorithms as well. Our hybrid CPU/GPU version of A3C, based on TensorFlow, achieves a significant speed up compared to a CPU implementation; we make it publicly available to other researchers at https://github.com/NVlabs/GA3C .

Key facts. Cited by 48 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Nov 2016.

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Citing papers per year: 2021: 15; 2022: 10; 2023: 6; 2024: 4; 2025: 11; 2026: 2.

48 papers.

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  1. 2025LLM Post-Training: A Deep Dive into Reasoning Large Language Modelscited by 135
  2. 2022A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learningcited by 83
  3. 2021Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Surveycited by 28
  4. 2021MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learningcited by 23
  5. 2022Lifelong Reinforcement Learning with Modulating Maskscited by 22
  6. 2021A Survey on Deep Reinforcement Learning for Audio-Based Applicationscited by 17
  7. 2024Reinforcing Language Agents via Policy Optimization with Action Decompositioncited by 16
  8. 2024Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Processcited by 11
  9. 2025Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Taskscited by 11
  10. 2021Agent-Centric Relation Graph for Object Visual Navigationcited by 10
  11. 2025Benchmarking Quantum Reinforcement Learningcited by 10
  12. 2022Robust Knowledge Adaptation for Dynamic Graph Neural Networkscited by 9
36 more
  1. 2024Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Surveycited by 8
  2. 2021GST: Group-Sparse Training for Accelerating Deep Reinforcement Learningcited by 7
  3. 2023Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platformcited by 7
  4. 2021Deep Reinforcement Learning for Conservation Decisionscited by 5
  5. 2021Costly Features Classification using Monte Carlo Tree Searchcited by 4
  6. 2022Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolboxcited by 4
  7. 2023Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Educationcited by 4
  8. 2025Putting on the Thinking Hats: A Survey on Chain of Thought Fine-tuning from the Perspective of Human Reasoning Mechanismcited by 4
  9. 2021Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precisioncited by 3
  10. 2023A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learningcited by 3
  11. 2021Coding for Distributed Multi-Agent Reinforcement Learningcited by 2
  12. 2022A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applicationscited by 2
  13. 2023Deep Reinforcement Learning for ESG financial portfolio managementcited by 2
  14. 2021An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarioscited by 1
  15. 2021Ensemble Consensus-based Representation Deep Reinforcement Learning for Hybrid FSO/RF Communication Systemscited by 1
  16. 2022Efficient Distributed Framework for Collaborative Multi-Agent Reinforcement Learningcited by 1
  17. 2022Scaling up Stochastic Gradient Descent for Non-convex Optimisationcited by 1
  18. 2022WILD-SCAV: Benchmarking FPS Gaming AI on Unity3D-based Environmentscited by 1
  19. 2025Learning more with the same effort: how randomization improves the robustness of a robotic deep reinforcement learning agentcited by 1
  20. 2025Reinforcement Learning for Game-Theoretic Resource Allocation on Graphscited by 1
  21. 2025ReaCritic: Reasoning Transformer-based DRL Critic-model Scaling For Wireless Networkscited by 1
  22. 2025Improving Aviation Safety Analysis: Automated HFACS Classification Using Reinforcement Learning with Group Relative Policy Optimizationcited by 1
  23. 2021A review of motion planning algorithms for intelligent roboticscited by 0
  24. 2021Optimal Path Planning of Autonomous Marine Vehicles in Stochastic Dynamic Ocean Flows using a GPU-Accelerated Algorithmcited by 0
  25. 2021A Practical Adversarial Attack on Contingency Detection of Smart Energy Systemscited by 0
  26. 2021Human-Level Control without Server-Grade Hardwarecited by 0
  27. 2022Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategiescited by 0
  28. 2022AcceRL: Policy Acceleration Framework for Deep Reinforcement Learningcited by 0
  29. 2023DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithmcited by 0
  30. 2023Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulationcited by 0
  31. 2024Adaptive BESS and Grid Setpoints Optimization: A Model-Free Framework for Efficient Battery Management under Dynamic Tariff Pricingcited by 0
  32. 2025Integrating Human Feedback into a Reinforcement Learning-Based Framework for Adaptive User Interfacescited by 0
  33. 2025Adaptive Social Metaverse Streaming based on Federated Multi-Agent Deep Reinforcement Learningcited by 0
  34. 2025Reinforcement Learning Based Traffic Signal Design to Minimize Queue Lengthscited by 0
  35. 2026Boosting Deep Reinforcement Learning with Semantic Knowledge for Robotic Manipulatorscited by 0
  36. 2026Improving Heart-Focused Medical Question Answering in LLMs via Variance-Aware Rubric Rewards with GRPOcited by 0