New blog post on Catan

- Closes #11
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Nemo 2022-04-12 14:08:01 +05:30
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# Contributing
Pull requests are welcome, as long as they follow these simple guidelines:
Suggestions for new resources are welcome, as long as they follow these simple
guidelines:
1. Links must be to the DOI (or arXiV), or the canonical reference page in that order. Prefer the original title as much as possible.
1. Try to avoid low-information research (posters/presentations) unless the topic is not covered elsewhere in a better medium.
1. Links must be to the DOI (or arXiV), or the canonical reference page in that
order. Prefer the original title as much as possible.
1. Try to avoid low-information research (posters/presentations) unless the
topic is not covered elsewhere in a better medium.
Please note we have a code of conduct, please follow it in all your interactions with the project.
Please note we have a code of conduct, please follow it in all your interactions
with the project.
### How to make a submission
You can send us a link by [creating a new issue](https://github.com/captn3m0/boardgame-research/issues/new/choose) on GitHub
or [sending me an email](https://captnemo.in/contact/) with the details.
You can send us a link by
[creating a new issue](https://github.com/captn3m0/boardgame-research/issues/new/choose)
on GitHub or [sending me an email](https://captnemo.in/contact/) with the
details.

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@ -306,6 +306,7 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub](
- [Strategic Dialogue Management via Deep Reinforcement Learning](http://arxiv.org/abs/1511.08099) (journalArticle)
- [Strategic Dialogue Management via Deep Reinforcement Learning](http://arxiv.org/abs/1511.08099) (journalArticle)
- [Analysis of 'The Settlers of Catan' Using Markov Chains](https://repository.tcu.edu/handle/116099117/49062) (thesis)
- [Learning to Play Settlers of Catan with Deep Reinforcement Learning](https://settlers-rl.github.io/) (blogPost)
# Shobu
- [Shobu AI Playground](https://github.com/JayWalker512/Shobu) (computerProgram)

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@ -8940,6 +8940,9 @@ guaranteed decent high score. The algorithm got a lowest score of 79 and a
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