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A reinforcement learning agent capable of playing blackjack. A python implementation of easy21 assignment of reinforcement learning course by David Silver

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Easy21

Discussion

A complete description of the math: https://github.com/XingyuHe/Easy21/blob/master/ProjectMath.pdf

Usage

Install required packages by running

pip install -r requirements.txt

To use Markov Decision Process and Monte Carlo to estimate state action value function, run

python Markov_Decision_Process.py

To use Monte Carlo Control to estimate state action value function, run

python Monte_Carlo_Control.py

Results

Algorithm State-Action Value Function Policy (yellow - hit, purple - stay)
Markov Decision Process alt text alt text
Monte Carlo Control (Linearly Decreasing Epsilon) alt text alt text

Evolution of Monte Carlo Control

Algorithm State-Action Value Function Policy (yellow - hit, purple - stay)
Epsilon = 0 alt text alt text
Epsilon = 1 alt text alt text
Linearly Decreasing Epsilon alt text alt text

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A reinforcement learning agent capable of playing blackjack. A python implementation of easy21 assignment of reinforcement learning course by David Silver

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