[PRE REVIEW]: Reinforcement Learning: A Comprehensive Open-Source Course

[editorialbot]

Submitting author: @XyDrKRulof (Darius Jakobeit)
Repository: https://github.com/upb-lea/reinforcement_learning_course_materials
Branch with paper.md (empty if default branch):
Version: 2023 edition - v1
Editor: Pending
Reviewers: Pending
Managing EiC: Lorena Barba

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Markdown: [![status](https://jose.theoj.org/papers/8d90df795c6c49a039c89870ec1d7383/status.svg)](https://jose.theoj.org/papers/8d90df795c6c49a039c89870ec1d7383)

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Software report:

github.com/AlDanial/cloc v 1.88  T=2.23 s (88.8 files/s, 121841.8 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
SVG                             94            220             83         196400
TeX                             18            688           1442           8315
Jupyter Notebook                43              0          51980           7238
MATLAB                          16            457            405           2303
Markdown                        18            100              0            480
Python                           8            349            688            468
YAML                             1              7             10             32
-------------------------------------------------------------------------------
SUM:                           198           1821          54608         215236
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1516

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.5281/zenodo.3509134 is OK
- 10.25080/Majora-92bf1922-00a is OK
- 10.5281/zenodo.8127026 is OK
- 10.1038/nature16961 is OK
- 10.1038/s41586-019-1724-z is OK
- 10.1109/OJPEL.2021.3065877 is OK
- 10.1177/0278364913495721 is OK
- 10.1109/FES57669.2023.10182718 is OK
- 10.1109/OJIES.2021.3075521 is OK

MISSING DOIs

- None

INVALID DOIs

- https://doi.org/10.1016/j.artmed.2020.101964 is INVALID because of 'https://doi.org/' prefix

[XyDrKRulof]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.5281/zenodo.3509134 is OK
- 10.25080/Majora-92bf1922-00a is OK
- 10.5281/zenodo.8127026 is OK
- 10.1038/nature16961 is OK
- 10.1038/s41586-019-1724-z is OK
- 10.1109/OJPEL.2021.3065877 is OK
- 10.1177/0278364913495721 is OK
- 10.1016/j.artmed.2020.101964 is OK
- 10.1109/FES57669.2023.10182718 is OK
- 10.1109/OJIES.2021.3075521 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Reinforcement Learning: An Introduction
- No DOI given, and none found for title: Lectures on Reinforcement Learning
- No DOI given, and none found for title: Jupyter Notebooks – a publishing format for reprod...
- No DOI given, and none found for title:  TensorFlow: Large-Scale Machine Learning on Heter...
- No DOI given, and none found for title: PyTorch: An Imperative Style, High-Performance Dee...
- No DOI given, and none found for title: OpenAI Gym
- No DOI given, and none found for title: Stable-Baselines3: Reliable Reinforcement Learning...
- No DOI given, and none found for title: Mastering Chess and Shogi by Self-Play with a Gene...
- No DOI given, and none found for title: Playing Atari with Deep Reinforcement Learning
- No DOI given, and none found for title: Training a Helpful and Harmless Assistant with Rei...
- No DOI given, and none found for title: Applications of Reinforcement Learning in Finance ...
- No DOI given, and none found for title: An Efficient Deep Reinforcement Learning Model for...
- No DOI given, and none found for title: API design for machine learning software: experien...

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[XyDrKRulof]

Based on the list of possible reviewers I would - based on their expertise - suggest abuccts, ahmaurya, krother or lebebr01.