Skip to content

ruqoyyasadiq/deep_RL-multi-arm-bandit-exploration

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Multi-arm Bandits Exploration

This is an bandit experiment that implements different exploration techniques for a 10-arm testbed as described in the Reinforcement Learning Book by Sutton & Barto.

The exploration techniques covered include:

  • ε-greedy
  • Optimistic Initialization
  • UCB Exploration
  • Boltzmann (Softmax) Exploration

This experiment further compares the different exploration techniques and concludes on which is better to use in different settings.

About

This is an implementation of the Reinforcement Learning multi-arm-bandit experiment using different exploration techniques.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages