mlsanityData to 7 Oct 2026

A Survey on Quantum Reinforcement Learning

arXiv 2211.03464 ↗First posted 7 Nov 2022quant-ph cs.LGcited by 50

Not on the map. Why?

Abstract (arXiv)

Quantum reinforcement learning is an emerging field at the intersection of quantum computing and machine learning. While we intend to provide a broad overview of the literature on quantum reinforcement learning - our interpretation of this term will be clarified below - we put particular emphasis on recent developments. With a focus on already available noisy intermediate-scale quantum devices, these include variational quantum circuits acting as function approximators in an otherwise classical reinforcement learning setting. In addition, we survey quantum reinforcement learning algorithms based on future fault-tolerant hardware, some of which come with a provable quantum advantage. We provide both a birds-eye-view of the field, as well as summaries and reviews for selected parts of the literature.

Key facts. Cited by 50 papers in the map (data through 7 Oct 2026). Builds on 51 of its 148 references that are in the map. First posted on arXiv 7 Nov 2022.

Builds on

51 of 148 references.

References · 51

  1. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  2. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  3. 2018Soft Actor-Critic Algorithms and Applicationscited by 1,179
  4. 2017Reinforcement Learning with Deep Energy-Based Policiescited by 659
  5. 2018Attention, Learn to Solve Routing Problems!cited by 646
  6. 2017A Brief Survey of Deep Reinforcement Learningcited by 466
  7. 2017Distributional Reinforcement Learning with Quantile Regressioncited by 464
  8. 2020The power of quantum neural networkscited by 377
  9. 2019Parameterized quantum circuits as machine learning modelscited by 330
  10. 2020The effect of data encoding on the expressive power of variational quantum machine learning modelscited by 328
  11. 2020A rigorous and robust quantum speed-up in supervised machine learningcited by 270
  12. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
38 more
  1. 2020Absence of Barren Plateaus in Quantum Convolutional Neural Networkscited by 124
  2. 2020Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Modelcited by 108
  3. 2021Parametrized quantum policies for reinforcement learningcited by 87
  4. 2016Quantum-enhanced machine learningcited by 79
  5. 2018Continuous-variable quantum neural networkscited by 74
  6. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  7. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  8. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  9. 2018The power of block-encoded matrix powers: improved regression techniques via faster Hamiltonian simulationcited by 30
  10. 2019Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problemscited by 30
  11. 2022Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Designcited by 25
  12. 2021Quantum Algorithms for Reinforcement Learning with a Generative Modelcited by 24
  13. 2021Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementationcited by 23
  14. 2022Quantum Multi-Agent Meta Reinforcement Learningcited by 23
  15. 2020Quantum exploration algorithms for multi-armed banditscited by 22
  16. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  17. 2016Reinforcement Learning Using Quantum Boltzmann Machinescited by 19
  18. 2022Quantum Reinforcement Learning via Policy Iterationcited by 19
  19. 2022Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regretscited by 19
  20. 2021Deep Reinforcement Learning with Quantum-inspired Experience Replaycited by 18
  21. 2018A Quantum Interior Point Method for LPs and SDPscited by 17
  22. 2021Variational Quantum Soft Actor-Criticcited by 14
  23. 2022Uncovering Instabilities in Variational-Quantum Deep Q-Networkscited by 14
  24. 2022Incremental Data-Uploading for Full-Quantum Classificationcited by 13
  25. 2015Framework for learning agents in quantum environmentscited by 9
  26. 2017Multiqubit and multilevel quantum reinforcement learning with quantum technologiescited by 9
  27. 2017Basic protocols in quantum reinforcement learning with superconducting circuitscited by 8
  28. 2019Photonic architecture for reinforcement learningcited by 8
  29. 2018Quantum Speedups for Exponential-Time Dynamic Programming Algorithmscited by 6
  30. 2019Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problemscited by 6
  31. 2020Intelligent Trajectory Planning in UAV-mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspectivecited by 6
  32. 2017Quantum Artificial Life in an IBM Quantum Computercited by 5
  33. 2021Short Quantum Circuits in Reinforcement Learning Policies for the Vehicle Routing Problemcited by 5
  34. 2022Quantum bandit with amplitude amplification exploration in an adversarial environmentcited by 5
  35. 2015Projective simulation with generalizationcited by 4
  36. 2017Speeding-up the decision making of a learning agent using an ion trap quantum processorcited by 4
  37. 2018Measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti quantum computercited by 3
  38. 2019On the convergence of projective-simulation-based reinforcement learning in Markov decision processescited by 3

50 most cited of 51 All 51 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 9; 2024: 15; 2025: 19; 2026: 5.

50 papers.

Sort:

  1. 2023Quantum Deep Hedgingcited by 22
  2. 2022Quantum Policy Gradient Algorithm with Optimized Action Decodingcited by 21
  3. 2023Asynchronous training of quantum reinforcement learningcited by 20
  4. 2023Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learningcited by 17
  5. 2022Quantum policy gradient algorithmscited by 15
  6. 2023Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applicationscited by 14
  7. 2023Quantum Bayesian Optimizationcited by 12
  8. 2024VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainabilitycited by 12
  9. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 12
  10. 2023Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regretcited by 9
  11. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  12. 2025Benchmarking Quantum Reinforcement Learningcited by 9
38 more
  1. 2025A Primer on Quantum Machine Learningcited by 9
  2. 2024A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learningcited by 7
  3. 2024An Introduction to Quantum Reinforcement Learning (QRL)cited by 7
  4. 2025Learning to Program Quantum Measurements for Machine Learningcited by 7
  5. 2023Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learningcited by 6
  6. 2025Quantum computing and artificial intelligence: status and perspectivescited by 5
  7. 2025Quantum Reinforcement Learning by Adaptive Non-local Observablescited by 5
  8. 2025Quantum-enhanced Computer Vision: Going Beyond Classical Algorithmscited by 5
  9. 2024Model-based Offline Quantum Reinforcement Learningcited by 4
  10. 2024Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rulecited by 4
  11. 2024Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularizationcited by 4
  12. 2024Fourier Analysis of Variational Quantum Circuits for Supervised Learningcited by 4
  13. 2025Quantum Lipschitz Banditscited by 4
  14. 2025Quantum Long Short-term Memory with Differentiable Architecture Searchcited by 4
  15. 2023BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploadingcited by 3
  16. 2024Quantum Artificial Intelligence: A Brief Surveycited by 3
  17. 2023Quantum deep Q learning with distributed prioritized experience replaycited by 2
  18. 2024Comprehensive Library of Variational LSE Solverscited by 2
  19. 2025Quantum AIXI: Universal Intelligence via Quantum Informationcited by 2
  20. 2025Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexitiescited by 2
  21. 2026Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuitscited by 2
  22. 2026Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptationcited by 2
  23. 2024Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisationcited by 1
  24. 2025Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correctioncited by 1
  25. 2025Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environmentscited by 1
  26. 2024Quantum Algorithms: A New Frontier in Financial Crime Preventioncited by 0
  27. 2024Quantum Reinforcement Learning in Non-Abelian Environments: Unveiling Novel Formulations and Quantum Advantage Explorationcited by 0
  28. 2024Hybrid Classical-Quantum architecture for vectorised image classification of hand-written sketchescited by 0
  29. 2025CutReg: A loss regularizer for enhancing the scalability of QML via adaptive circuit cuttingcited by 0
  30. 2025From Classical Data to Quantum Advantage -- Quantum Policy Evaluation on Quantum Hardwarecited by 0
  31. 2025Hybrid Quantum-Classical Policy Gradient for Adaptive Control of Cyber-Physical Systems: A Comparative Study of VQC vs. MLPcited by 0
  32. 2025Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learningcited by 0
  33. 2025Formal Verification of Noisy Quantum Reinforcement Learning Policiescited by 0
  34. 2025Variational Quantum Rainbow Deep Q-Network for Optimizing Resource Allocation Problemcited by 0
  35. 2025QAISim: A Toolkit for Modeling and Simulation of AI in Quantum Cloud Computing Environmentscited by 0
  36. 2026Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimizationcited by 0
  37. 2026Enhanced Reinforcement Learning-based Process Synthesis via Quantum Computingcited by 0
  38. 2026Staged Hybridisation for Visual Quantum Reinforcement Learning via Knowledge Distillationcited by 0