Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory search

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Su, Thet Htar, Shresthamali, Shaswot, Kondo, Masaaki
Format:	Preprint
Published:	2024
Subjects:	Quantum Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimization
by: Su, Thet Htar, et al.
Published: (2025)

Q-fid: Quantum Circuit Fidelity Improvement with LSTM Networks
by: Mao, Yikai, et al.
Published: (2023)

Q-gen: A Parameterized Quantum Circuit Generator
by: Mao, Yikai, et al.
Published: (2024)

DAISM: Digital Approximate In-SRAM Multiplier-based Accelerator for DNN Training and Inference
by: Sonnino, Lorenzo, et al.
Published: (2023)

Reinforcement learning-based architecture search for quantum machine learning
by: Rapp, Frederic, et al.
Published: (2024)

Reinforcement learning-assisted quantum architecture search for variational quantum algorithms
by: Kundu, Akash
Published: (2024)

Reinforcement learning for quantum processes with memory
by: Lumbreras, Josep, et al.
Published: (2026)

Continuous optimization by quantum adaptive distribution search
by: Morimoto, Kohei, et al.
Published: (2023)

Discovery of Optimal Quantum Error Correcting Codes via Reinforcement Learning
by: Su, Vincent Paul, et al.
Published: (2023)

Benchmarking Quantum Reinforcement Learning
by: Meyer, Nico, et al.
Published: (2025)

Quantum Kolmogorov-Arnold networks by combining quantum signal processing circuits
by: Daskin, Ammar
Published: (2024)

A Survey on Quantum Reinforcement Learning
by: Meyer, Nico, et al.
Published: (2022)

Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
by: Lee, Yu-Ting, et al.
Published: (2026)

Reinforcement Learning for Variational Quantum Circuits Design
by: Foderà, Simone, et al.
Published: (2024)

Minor Embedding for Quantum Annealing with Reinforcement Learning
by: Nembrini, Riccardo, et al.
Published: (2025)

Challenges for Reinforcement Learning in Quantum Circuit Design
by: Altmann, Philipp, et al.
Published: (2023)

Robust Iterative Learning Hidden Quantum Markov Models
by: Ning, Ning
Published: (2025)

Variational decision diagrams for quantum-inspired machine learning applications
by: Vargas-Calderón, Vladimir, et al.
Published: (2025)

Quantum Compiling with Reinforcement Learning on a Superconducting Processor
by: Wang, Z. T., et al.
Published: (2024)

Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement Learning
by: Li, Linsen, et al.
Published: (2024)

Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learning
by: Gerlach, Thore, et al.
Published: (2025)

Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
by: Yeung, Richie, et al.
Published: (2026)

Quantum Logic Gate Synthesis as a Markov Decision Process
by: Alam, M. Sohaib, et al.
Published: (2019)

Online learning of quantum processes
by: Raza, Asad, et al.
Published: (2024)

Provable and scalable quantum Gaussian processes for quantum learning
by: Jäger, Jonas, et al.
Published: (2026)

Hamiltonian-based Quantum Reinforcement Learning for Neural Combinatorial Optimization
by: Kruse, Georg, et al.
Published: (2024)

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
by: Meyer, Nico, et al.
Published: (2024)

Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesis
by: Theißinger, Lukas, et al.
Published: (2026)

Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
by: Mills, Daniel, et al.
Published: (2026)

Classical Verification of Quantum Learning Advantages with Noises
by: Ma, Yinghao, et al.
Published: (2024)

Des-q: a quantum algorithm to provably speedup retraining of decision trees
by: Kumar, Niraj, et al.
Published: (2023)

Differentiating and Integrating ZX Diagrams with Applications to Quantum Machine Learning
by: Wang, Quanlong, et al.
Published: (2022)

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations
by: Tashev, Pavel, et al.
Published: (2024)

A Strategy for Preparing Quantum Squeezed States Using Reinforcement Learning
by: Zhao, X. L., et al.
Published: (2024)

Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study
by: Stenzel, Gerhard, et al.
Published: (2026)

Dissecting Quantum Reinforcement Learning: A Systematic Evaluation of Key Components
by: Lazaro, Javier, et al.
Published: (2025)

TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture search
by: Kundu, Akash, et al.
Published: (2025)

A unifying primary framework for quantum graph neural networks from quantum graph states
by: Daskin, Ammar
Published: (2024)

Quantum Deep Reinforcement Learning for Robot Navigation Tasks
by: Hohenfeld, Hans, et al.
Published: (2022)

Extending a Quantum Reinforcement Learning Exploration Policy with Flags to Connect Four
by: Santos, Filipe, et al.
Published: (2025)