Skip to content

Reproduction of Curiosity-driven Exploration by Self-supervised Prediction in PyTorch

License

Notifications You must be signed in to change notification settings

qfettes/CuriosityDrivenExplorationBySelfSupervisedPrediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

26 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Reproduction of "Curiosity-driven Exploration for Deep Reinforcement Learning" with PyTorch

This is a PyTorch reproduction of the ICML 2017 paper "Curiosity-driven Exploration for Deep Reinforcement Learning." It uses A2C rather than A3C. It only allows evaluation on the SuperMarioBros environment right now. Look at the original Tensorflow implementation here.

To Train

python3 a2c_devel.py --recurrent-policy

Requirements:

Acknowledgements:

  • Credit to @pathak22 For their publicly available original implementation
  • Credit to @baselines for templates for the environment wrappers
  • Credit to @sadeqa for the template for ProcessFrameMario() wrapper
  • Credit to @ikostrikov for A2C, GAE, PPO and inspiration for plotting code implementation