Skip to content

Implementation of several reinforcement learning algorithms used to play a variation of blackjack

Notifications You must be signed in to change notification settings

WillGrayMSU/Reinforcement-Learning-in-Blackjack

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Reinforcement-Learning-in-Blackjack

Implementation of several reinforcement learning algorithms used to play a variation of blackjack

In order to run all the algorithms just run main.py.

This will execute test_all_algorithms() function which runs MC, SARSA and Linear Function Approximation with SARSA with plots showing the results.

Details about other modules:

  • environment.py - contains the step() function and the implementation of the environment
  • rl_algorithms - contains MC, SARSA and Linear Function Approximation
  • plotting.py - contains functions to plot value function, SARSA and LFA results
  • policies.py - place to put the policies, at the moment contains just epsilon greedy policy
  • utilities.py - calculation of mean squared error and conversion of state to feature vector for LFA

About

Implementation of several reinforcement learning algorithms used to play a variation of blackjack

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%