Blackjack-21
rlcard
| Blackjack-21 | rlcard | |
|---|---|---|
| 6 | 5 | |
| 8 | 2,719 | |
| - | 2.6% | |
| 1.8 | 6.2 | |
| over 2 years ago | 3 months ago | |
| Python | Python | |
| MIT License | MIT License |
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Blackjack-21
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I made Blackjack 21 in Python!
Releases / Latest changes
Link to project
TODO List: Check out the issues page for this project: https://github.com/JordanLeich/Blackjack-21/issues/3
I took into account all of the changes you suggested and I applied the majority of them to the project. I left out some of the suggested changes as I either didn't agree with a proposed change, a suggestion was either irrelevant, or didn't matter to me. Feel free to check out the updated project here.
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I made Blackjack 21 using Python!
u/redditonlyforu I applied all of the changes you suggested but I'm stuck on figuring out how to work on this class correctly without using any global statements, if you could take a look at the updated blackjack.py file I have on GitHub and possibly create a pull request fixing and changing it so I could see how to properly do it. Here is the link to the file. With the way it is currently, the player and dealer cards are not function properly and some of the values such as user balances and such are also not working correctly and it is either because I removed all the global statements or its from the class being created.
rlcard
- [P] Looking for RL or rules-based No-Limit Hold 'Em Work
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Self play environments
Hi. I’ve decided to do a project to adapt an rl library to support self-play. This is a project so I can teach myself more about building rl systems. I’ve been considering working with the environment system from rlcard https://github.com/datamllab/rlcard/ but wonder if there are other more widely-used self play environment libraries. Thanks.
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[Project] Making a Poker AI - having trouble with the form of ML to make smart / strong decisions
Can you point me to some active forums for poker bot building? I can only find github repo like https://github.com/datamllab/rlcard, which is mostly reinforcement learning. Whereas SoTA approach like Pluribus is more about game theory.
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8+ Reinforcement Learning Project Ideas
Build a Poker bot with RLCard
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What sort of algorithm should I use ? Incomplete information, card game. (Flowchart for reference)
Probably the easiest way for you to get started is to implement your game on an open source RL framework that has working implementations of some basic CFR variations as well as some other self-play algorithms such as NFSP. OpenSpiel and RLCard are two that I am aware of. Depending on the complexity of your game and how strong your agent needs to play, you might be satisfied with the performance you get using by one of these frameworks.
What are some alternatives?
cli-game-scripts - Minimal Python game script. Works foremost in xfce4-terminal and Gnome terminal
gym - A toolkit for developing and comparing reinforcement learning algorithms.
freebj - Free and open-source Blackjack strategy simulator in Rust
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Casino_games
mjai-reviewer - 🔍🀄️ Review mahjong game log with mjai-compatible mahjong AI.
terminal-blackjack - A terminal based Blackjack game written in Python.
Poker - Fully functional Pokerbot that works on PartyPoker, PokerStars and GGPoker, scraping tables with Open-CV (adaptable via gui) or neural network and making decisions based on a genetic algorithm and montecarlo simulation for poker equity calculation. Binaries can be downloaded with this link:
MonsterHunterPortable3rdHDRemake - Personal fork of a texture upscaling project for PSP's Monster Hunter Portable 3rd
shengji - An online version of shengji (a.k.a. tractor) and zhaopengyou (a.k.a. Finding Friends)
new-world-fishing-bot - user friendly python script who is able to catch fish in the game New World
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.