mlsanityData to 7 Oct 2026

Quantum deep Q learning with distributed prioritized experience replay

arXiv 2304.09648 ↗First posted 19 Apr 2023quant-ph cs.AI cs.DCcited by 2

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Abstract (arXiv)

This paper introduces the QDQN-DPER framework to enhance the efficiency of quantum reinforcement learning (QRL) in solving sequential decision tasks. The framework incorporates prioritized experience replay and asynchronous training into the training algorithm to reduce the high sampling complexities. Numerical simulations demonstrate that QDQN-DPER outperforms the baseline distributed quantum Q learning with the same model architecture. The proposed framework holds potential for more complex tasks while maintaining training efficiency.

Key facts. Cited by 2 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 19 Apr 2023.

Builds on

29 of 47 references.

References · 29

  1. 2016OpenAI Gymcited by 1,684
  2. 2015Prioritized Experience Replaycited by 1,070
  3. 2018Distributed Prioritized Experience Replaycited by 260
  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. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  8. 2021The Dawn of Quantum Natural Language Processingcited by 60
  9. 2020Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognitioncited by 56
  10. 2021Quantum Federated Learning with Quantum Datacited by 53
  11. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  12. 2022A Survey on Quantum Reinforcement Learningcited by 50
17 more
  1. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  2. 2022When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computingcited by 40
  3. 2020Quantum reinforcement learning in continuous action spacecited by 27
  4. 2021QTN-VQC: An End-to-End Learning framework for Quantum Neural Networkscited by 27
  5. 2022Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Designcited by 25
  6. 2022Quantum Multi-Agent Meta Reinforcement Learningcited by 23
  7. 2022Quantum deep recurrent reinforcement learningcited by 23
  8. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  9. 2022Quantum Policy Gradient Algorithm with Optimized Action Decodingcited by 21
  10. 2023Asynchronous training of quantum reinforcement learningcited by 20
  11. 2022Quantum Reinforcement Learning via Policy Iterationcited by 19
  12. 2022Quantum policy gradient algorithmscited by 15
  13. 2021Variational Quantum Soft Actor-Criticcited by 14
  14. 2022Uncovering Instabilities in Variational-Quantum Deep Q-Networkscited 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

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2023Efficient quantum recurrent reinforcement learning via quantum reservoir computingcited by 14
  2. 2024Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learningcited by 2