mlsanityData to 13 Oct 2026

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach

arXiv 2501.16243 ↗First posted 27 Jan 2025quant-ph cs.AI stat.MLcited by 4

On the map: Deep reinforcement learning methods → Quantum reinforcement learning

Abstract (arXiv)

We address the problem of quantum reinforcement learning (QRL) under model-free settings with quantum oracle access to the Markov Decision Process (MDP). This paper introduces a Quantum Natural Policy Gradient (QNPG) algorithm, which replaces the random sampling used in classical Natural Policy Gradient (NPG) estimators with a deterministic gradient estimation approach, enabling seamless integration into quantum systems. While this modification introduces a bounded bias in the estimator, the bias decays exponentially with increasing truncation levels. This paper demonstrates that the proposed QNPG algorithm achieves a sample complexity of tildeO(ε-1.5) for queries to the quantum oracle, significantly improving the classical lower bound of tildeO(ε-2) for queries to the MDP.

Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). Placed in Quantum reinforcement learning, one of 15 directions in Deep reinforcement learning methods. Builds on 22 of its 38 references that are in the map. First posted on arXiv 27 Jan 2025.

Builds on

22 of 38 references.

References · 22

  1. 2019On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shiftcited by 174
  2. 2019Neural Policy Gradient Methods: Global Optimality and Rates of Convergencecited by 158
  3. 2019Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policiescited by 117
  4. 2022An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methodscited by 64
  5. 2019Sample Efficient Policy Gradient Methods with Recursive Variance Reductioncited by 59
  6. 2019DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learningcited by 54
  7. 2021Quantum Algorithms for Reinforcement Learning with a Generative Modelcited by 24
  8. 2023Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processescited by 24
  9. 2020Quantum exploration algorithms for multi-armed banditscited by 22
  10. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  11. 2022Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regretscited by 19
  12. 2022Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithmcited by 19
10 more
  1. 2020Quantum Banditscited by 18
  2. 2021Near-Optimal Quantum Algorithms for Multivariate Mean Estimationcited by 16
  3. 2021Quantum Sub-Gaussian Mean Estimatorcited by 15
  4. 2022Quantum policy gradient algorithmscited by 15
  5. 2023Quantum speedups for stochastic optimizationcited by 12
  6. 2024Sample-Efficient Constrained Reinforcement Learning with General Parameterizationcited by 11
  7. 2023Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regretcited by 9
  8. 2023Quantum Heavy-tailed Banditscited by 8
  9. 2024Reinforced Sequential Decision-Making for Sepsis Treatment: The POSNEGDM Framework with Mortality Classifier and Transformercited by 6
  10. 2023Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processescited by 3

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learningcited by 6
  2. 2025Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environmentscited by 1
  3. 2026Mitigating Bias in Low-SNR Financial Reinforcement Learning via Quantum Representationscited by 0
  4. 2026Qubit-Efficient Quantum Search for Hyperdimensional Decomposition via Logarithmic Encodingcited by 0