A survey on quantum reinforcement learning
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 …
computing and machine learning. While we intend to provide a broad overview of the …
Variational Gibbs state preparation on noisy intermediate-scale quantum devices
The preparation of an equilibrium thermal state of a quantum many-body system on noisy
intermediate-scale quantum (NISQ) devices is an important task in order to extend the range …
intermediate-scale quantum (NISQ) devices is an important task in order to extend the range …
Asynchronous training of quantum reinforcement learning
SYC Chen - Procedia Computer Science, 2023 - Elsevier
The development of quantum machine learning (QML) has received a lot of interest recently
thanks to developments in both quantum computing (QC) and machine learning (ML). One …
thanks to developments in both quantum computing (QC) and machine learning (ML). One …
Efficient dimensionality reduction strategies for quantum reinforcement learning
Quantum neural networks constitute one of the most promising applications of Quantum
Machine Learning, as they leverage both the capabilities of classical neural networks and …
Machine Learning, as they leverage both the capabilities of classical neural networks and …
Variational gibbs state preparation on NISQ devices
M Consiglio, J Settino, A Giordano… - arXiv preprint arXiv …, 2023 - arxiv.org
The preparation of an equilibrium thermal state of a quantum many-body system on noisy
intermediate-scale (NISQ) devices is an important task in order to extend the range of …
intermediate-scale (NISQ) devices is an important task in order to extend the range of …
Quantum deep Q-learning with distributed prioritized experience replay
SYC Chen - 2023 IEEE International Conference on Quantum …, 2023 - ieeexplore.ieee.org
This paper introduces the QDQN-DPER framework to enhance the efficiency of quantum
reinforcement learning (QRL) in solving sequential decision tasks. The framework …
reinforcement learning (QRL) in solving sequential decision tasks. The framework …
Enhancing Physical Education: A Dynamic Fuzzy Neural Network-Based Information Processing System Design
Q Zhang, O Sohaib - IEEE Access, 2024 - ieeexplore.ieee.org
With the advent of digital intelligent education, educational resources are expanding. In the
realm of physical education, data encompassing students' physical fitness test results, sports …
realm of physical education, data encompassing students' physical fitness test results, sports …
Deep Q-learning with hybrid quantum neural network on solving maze problems
Quantum computing holds great potential for advancing the limitations of machine learning
algorithms to handle higher dimensions of data and reduce overall training parameters in …
algorithms to handle higher dimensions of data and reduce overall training parameters in …
Enhancing distributed agent environments with quantum multi-agent systems and protocols
A Jenefa, K Vidhya, A Taurshia… - Multiagent and Grid …, 2024 - content.iospress.com
Abstract The utilization of Quantum Multi-Agent Systems (MAS) and Quantum Protocols in
distributed agent environments has gained attention due to the need for enhanced protocol …
distributed agent environments has gained attention due to the need for enhanced protocol …