mlsanityData to 7 Oct 2026

Quantum policy gradient algorithms

arXiv 2212.09328 ↗First posted 19 Dec 2022quant-ph cs.AI cs.LGcited by 15

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Abstract (arXiv)

Understanding the power and limitations of quantum access to data in machine learning tasks is primordial to assess the potential of quantum computing in artificial intelligence. Previous works have already shown that speed-ups in learning are possible when given quantum access to reinforcement learning environments. Yet, the applicability of quantum algorithms in this setting remains very limited, notably in environments with large state and action spaces. In this work, we design quantum algorithms to train state-of-the-art reinforcement learning policies by exploiting quantum interactions with an environment. However, these algorithms only offer full quadratic speed-ups in sample complexity over their classical analogs when the trained policies satisfy some regularity conditions. Interestingly, we find that reinforcement learning policies derived from parametrized quantum circuits are well-behaved with respect to these conditions, which showcases the benefit of a fully-quantum reinforcement learning framework.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 22 of its 46 references that are in the map. First posted on arXiv 19 Dec 2022.

Builds on

22 of 46 references.

References · 22

  1. 2019Parameterized quantum circuits as machine learning modelscited by 330
  2. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
  3. 2019Mean estimation and regression under heavy-tailed distributions--a surveycited by 133
  4. 2018Learning to Navigate in Cities Without a Mapcited by 103
  5. 2021Parametrized quantum policies for reinforcement learningcited by 87
  6. 2016Quantum-enhanced machine learningcited by 79
  7. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  8. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  9. 2022A Survey on Quantum Reinforcement Learningcited by 50
  10. 2019Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learningcited by 37
  11. 2020Quantum reinforcement learning in continuous action spacecited by 27
  12. 2021Quantum Algorithms for Reinforcement Learning with a Generative Modelcited by 24
10 more
  1. 2020Quantum exploration algorithms for multi-armed banditscited by 22
  2. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  3. 2022Quantum Policy Gradient Algorithm with Optimized Action Decodingcited by 21
  4. 2022Quantum Reinforcement Learning via Policy Iterationcited by 19
  5. 2021Near-Optimal Quantum Algorithms for Multivariate Mean Estimationcited by 16
  6. 2021Quantum Sub-Gaussian Mean Estimatorcited by 15
  7. 2022Policy Gradients using Variational Quantum Circuitscited by 15
  8. 2017Exponential improvements for quantum-accessible reinforcement learningcited by 7
  9. 2020Information-Theoretic Lower Bounds for Zero-Order Stochastic Gradient Estimationcited by 3
  10. 2019The Problem of Dynamic Programming on a Quantum Computercited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 4; 2025: 3; 2026: 2.

15 papers.

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  1. 2023Quantum Deep Hedgingcited by 22
  2. 2023Asynchronous training of quantum reinforcement learningcited by 20
  3. 2023Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regretcited by 9
  4. 2024Quantum Advantage Actor-Critic for Reinforcement Learningcited by 9
  5. 2023Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learningcited by 6
  6. 2024Trainability issues in quantum policy gradientscited by 4
  7. 2025Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approachcited by 4
  8. 2023Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processescited by 3
  9. 2023Quantum deep Q learning with distributed prioritized experience replaycited by 2
  10. 2024An unconditional distribution learning advantage with shallow quantum circuitscited by 2
  11. 2025Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexitiescited by 2
  12. 2025A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Modelcited by 1
3 more
  1. 2024On Quantum Natural Policy Gradientscited by 0
  2. 2026Mitigating Bias in Low-SNR Financial Reinforcement Learning via Quantum Representationscited by 0
  3. 2026Improved Quantum Algorithms for Reinforcement Learning Under a Generative Modelcited by 0