mlsanityData to 7 Oct 2026

Reinforcement Learning with Quantum Variational Circuits

arXiv 2008.07524 ↗First posted 15 Aug 2020quant-ph cs.LG stat.MLcited by 74

Not on the map. Why?

Abstract (arXiv)

The development of quantum computational techniques has advanced greatly in recent years, parallel to the advancements in techniques for deep reinforcement learning. This work explores the potential for quantum computing to facilitate reinforcement learning problems. Quantum computing approaches offer important potential improvements in time and space complexity over traditional algorithms because of its ability to exploit the quantum phenomena of superposition and entanglement. Specifically, we investigate the use of quantum variational circuits, a form of quantum machine learning. We present our techniques for encoding classical data for a quantum variational circuit, we further explore pure and hybrid quantum algorithms for DQN and Double DQN. Our results indicate both hybrid and pure quantum variational circuit have the ability to solve reinforcement learning tasks with a smaller parameter space. These comparison are conducted with two OpenAI Gym environments: CartPole and Blackjack, The success of this work is indicative of a strong future relationship between quantum machine learning and deep reinforcement learning.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Aug 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 12; 2022: 14; 2023: 13; 2024: 14; 2025: 12; 2026: 9.

74 papers.

Sort:

By area:

  1. 2021Parametrized quantum policies for reinforcement learningcited by 87
  2. 2021Federated Quantum Machine Learningcited by 82
  3. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 58
  4. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  5. 2022A Survey on Quantum Reinforcement Learningcited by 50
  6. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  7. 2022Equivariant quantum circuits for learning on weighted graphscited by 41
  8. 2021Quantum machine learning with differential privacycited by 30
  9. 2022Quantum Multi-Agent Meta Reinforcement Learningcited by 23
  10. 2022Quantum deep recurrent reinforcement learningcited by 23
  11. 2024Learning to Program Variational Quantum Circuits with Fast Weightscited by 23
  12. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
38 more
  1. 2023Quantum Deep Hedgingcited by 22
  2. 2021Hybrid Quantum-Classical Graph Convolutional Networkcited by 21
  3. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  4. 2021Quantum Self-Supervised Learningcited by 20
  5. 2023Asynchronous training of quantum reinforcement learningcited by 20
  6. 2022Quantum Reinforcement Learning via Policy Iterationcited by 19
  7. 2024Quantum Implicit Neural Representationscited by 16
  8. 2022Policy Gradients using Variational Quantum Circuitscited by 15
  9. 2022Quantum policy gradient algorithmscited by 15
  10. 2022Uncovering Instabilities in Variational-Quantum Deep Q-Networkscited by 14
  11. 2022Quantum Deep Reinforcement Learning for Robot Navigation Taskscited by 14
  12. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  13. 2023Efficient quantum recurrent reinforcement learning via quantum reservoir computingcited by 14
  14. 2025Toward Large-Scale Distributed Quantum Long Short-Term Memory with Modular Quantum Computerscited by 14
  15. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 13
  16. 2024VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainabilitycited by 12
  17. 2021Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designscited by 11
  18. 2023QUILT: Effective Multi-Class Classification on Quantum Computers Using an Ensemble of Diverse Quantum Classifierscited by 11
  19. 2024Quantum Advantage Actor-Critic for Reinforcement Learningcited by 9
  20. 2024Quantum Gradient Class Activation Map for Model Interpretabilitycited by 9
  21. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  22. 2025Benchmarking Quantum Reinforcement Learningcited by 9
  23. 2025A Primer on Quantum Machine Learningcited by 9
  24. 2021Optimizing Quantum Variational Circuits with Deep Reinforcement Learningcited by 8
  25. 2024QADQN: Quantum Attention Deep Q-Network for Financial Market Predictioncited by 8
  26. 2024A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learningcited by 7
  27. 2024An Introduction to Quantum Reinforcement Learning (QRL)cited by 7
  28. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
  29. 2025Learning to Program Quantum Measurements for Machine Learningcited by 7
  30. 2023Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperationcited by 6
  31. 2023Nav-Q: Quantum Deep Reinforcement Learning for Collision-Free Navigation of Self-Driving Carscited by 6
  32. 2023Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systemscited by 5
  33. 2025Quantum Reinforcement Learning by Adaptive Non-local Observablescited by 5
  34. 2022Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Codingcited by 4
  35. 2024Model-based Offline Quantum Reinforcement Learningcited by 4
  36. 2026Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learningcited by 4
  37. 2021Photonic Quantum Policy Learning in OpenAI Gymcited by 3
  38. 2022QuAnt: Quantum Annealing with Learnt Couplingscited by 3

50 most cited of 74 All 74 (JSON)