Quantum Reinforcement Learning with Quantum Photonics

Quantum machine learning has emerged as a promising paradigm that could accelerate machine learning calculations. Inside this field, quantum reinforcement learning aims at designing and building quantum agents that may exchange information with their environment and adapt to it, with the aim of achi...

Full description

Saved in:
Bibliographic Details
Published in:Photonics 2021-02, Vol.8 (2), p.33
Main Author: Lamata, Lucas
Format: Article
Language:English
Subjects:
Adaptation
Algorithms
Artificial intelligence
Learning algorithms
Machine learning
Photonics
Protocol
quantum communication
Quantum computing
quantum machine learning
quantum photonics
quantum reinforcement learning
quantum technologies
Reinforcement
Tomography
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Quantum machine learning has emerged as a promising paradigm that could accelerate machine learning calculations. Inside this field, quantum reinforcement learning aims at designing and building quantum agents that may exchange information with their environment and adapt to it, with the aim of achieving some goal. Different quantum platforms have been considered for quantum machine learning and specifically for quantum reinforcement learning. Here, we review the field of quantum reinforcement learning and its implementation with quantum photonics. This quantum technology may enhance quantum computation and communication, as well as machine learning, via the fruitful marriage between these previously unrelated fields.
ISSN:2304-6732
2304-6732
DOI:10.3390/photonics8020033