Skip to content

Applying reinforcement learning methods to a simple card game.

Notifications You must be signed in to change notification settings

arielfayol37/Easy21

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Read Reference Instructions.pdf

To be concise, This repository is a solution to reference instructions.pdf We create an environment(a game) and different RL (Reinforcement Learning) agents that can interact (play). The following are the three RL agents that have been implemented.

  • Monte Carlo
  • Backward-view Sarsa lambda
  • Backward-view Sarsa lambda using a linear function approximator

A human being can also play the game with or without the assist of any of the agents.

Releases

No releases published

Packages

No packages published

Languages