Published August 31, 2024 | Version v1
Software Open

Reproduction Package for "Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation" @QCE24

  • 1. ROR icon Regensburg University of Applied Sciences
  • 1. ROR icon University of Lübeck
  • 2. ROR icon Regensburg University of Applied Sciences

Description

With this reproduction package the results published in the paper "Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation" by Maja Franz, Tobias Winker, Sven Groppe and Wolfgang Mauerer, published at the IEEE International Conference on Quantum Computing and Engineering (QCE24), 2024, can be reproduced.

A preprint of the paper can be found on arXiv.

The source code is also available on GitHub

Artifacts:

  • qce24_repro.tar -- Prebuilt Docker image, load with "docker load -i qce24_repro.tar"
  • RL_for_JO.tar.gz -- compressed source code (same as on GitHub)

 

Files

Files (13.7 GB)

Name Size Download all
md5:e702c2bb3cadf994432165a9d960dc9a
13.4 GB Download
md5:d3370033bb5afcc5376c33385633d09f
279.4 MB Download

Additional details

Identifiers

Related works

Is metadata for
Preprint: arXiv:2405.07770 (arXiv)

Funding

Federal Ministry of Education and Research
quantum technologies—from basic research to market 13NI6092

Software

Repository URL
https://github.com/lfd/RL_for_JO
Programming language
Python , R , TeX
Development Status
Inactive