mlsanityData to 7 Oct 2026

Asynchronous training of quantum reinforcement learning

arXiv 2301.05096 ↗First posted 12 Jan 2023quant-ph cs.AI cs.DCcited by 20

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Abstract (arXiv)

The development of quantum machine learning (QML) has received a lot of interest recently thanks to developments in both quantum computing (QC) and machine learning (ML). One of the ML paradigms that can be utilized to address challenging sequential decision-making issues is reinforcement learning (RL). It has been demonstrated that classical RL can successfully complete many difficult tasks. A leading method of building quantum RL agents relies on the variational quantum circuits (VQC). However, training QRL algorithms with VQCs requires significant amount of computational resources. This issue hurdles the exploration of various QRL applications. In this paper, we approach this challenge through asynchronous training QRL agents. Specifically, we choose the asynchronous training of advantage actor-critic variational quantum policies. We demonstrate the results via numerical simulations that within the tasks considered, the asynchronous training of QRL agents can reach performance comparable to or superior than classical agents with similar model sizes and architectures.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 29 of its 47 references that are in the map. First posted on arXiv 12 Jan 2023.

Builds on

29 of 47 references.

References · 29

  1. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,218
  2. 2016OpenAI Gymcited by 1,684
  3. 2020Variational Quantum Algorithmscited by 687
  4. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
  5. 2020Quantum Long Short-Term Memorycited by 118
  6. 2021Federated Quantum Machine Learningcited by 82
  7. 2021Noisy intermediate-scale quantum (NISQ) algorithmscited by 79
  8. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  9. 2020Quantum Convolutional Neural Networks for High Energy Physics Data Analysiscited by 64
  10. 2021The Dawn of Quantum Natural Language Processingcited by 60
  11. 2020Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognitioncited by 56
  12. 2021Quantum Federated Learning with Quantum Datacited by 53
17 more
  1. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  2. 2022A Survey on Quantum Reinforcement Learningcited by 50
  3. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  4. 2022When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computingcited by 40
  5. 2020Quantum reinforcement learning in continuous action spacecited by 27
  6. 2021QTN-VQC: An End-to-End Learning framework for Quantum Neural Networkscited by 27
  7. 2022Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Designcited by 25
  8. 2022Quantum Multi-Agent Meta Reinforcement Learningcited by 23
  9. 2022Quantum deep recurrent reinforcement learningcited by 23
  10. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  11. 2022Quantum Policy Gradient Algorithm with Optimized Action Decodingcited by 21
  12. 2022Quantum Reinforcement Learning via Policy Iterationcited by 19
  13. 2022Quantum policy gradient algorithmscited by 15
  14. 2021Variational Quantum Soft Actor-Criticcited by 14
  15. 2022Quantum Deep Reinforcement Learning for Robot Navigation Taskscited by 14
  16. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  17. 2022Variational Quantum Soft Actor-Critic for Robotic Arm Controlcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 9; 2025: 6; 2026: 3.

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  1. 2024Quantum Architecture Search: A Surveycited by 31
  2. 2024Learning to Program Variational Quantum Circuits with Fast Weightscited by 23
  3. 2023Efficient quantum recurrent reinforcement learning via quantum reservoir computingcited by 14
  4. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 13
  5. 2024Quantum Advantage Actor-Critic for Reinforcement Learningcited by 9
  6. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  7. 2024eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channelscited by 7
  8. 2024An Introduction to Quantum Reinforcement Learning (QRL)cited by 7
  9. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
  10. 2025Learning to Program Quantum Measurements for Machine Learningcited by 7
  11. 2025Quantum Reinforcement Learning by Adaptive Non-local Observablescited by 5
  12. 2024Machine Learning Applications of Quantum Computing: A Reviewcited by 4
8 more
  1. 2025Q-Fusion: Diffusing Quantum Circuitscited by 4
  2. 2026Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learningcited by 4
  3. 2025Introduction to Quantum Machine Learning and Quantum Architecture Searchcited by 3
  4. 2023Quantum deep Q learning with distributed prioritized experience replaycited by 2
  5. 2024Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learningcited by 2
  6. 2026Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuitscited by 2
  7. 2025Quantum-Enhanced Forecasting for Deep Reinforcement Learning in Algorithmic Tradingcited by 1
  8. 2026Diagonal Adaptive Non-local Observables on Quantum Neural Networkscited by 0