Blackjack--Reinforcement-Learning

Teaching a bot how to play Blackjack using two techniques: Q-Learning and Deep Q-Learning.

The game used is OpenAI's gym environment. However, the blackjack game only consists of hitting and standing.

To fully obtain a working Blackjack bot, it would be necessary to add doubling down, splitting, and variation of bets to the game environment.

TODO

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
__pycache__		__pycache__
logs		logs
.gitignore		.gitignore
Blackjack- DQN (Only Hit or Stand).ipynb		Blackjack- DQN (Only Hit or Stand).ipynb
Blackjack- Q Learning (Doubling Down).ipynb		Blackjack- Q Learning (Doubling Down).ipynb
Blackjack-Q Learning (Only Hit or Stand) 100 Lines.ipynb		Blackjack-Q Learning (Only Hit or Stand) 100 Lines.ipynb
Blackjack-Q Learning (Only Hit or Stand).ipynb		Blackjack-Q Learning (Only Hit or Stand).ipynb
README.md		README.md
blackjackenv.py		blackjackenv.py
optimal_policy.csv		optimal_policy.csv

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