Kaixhin/ ACER
Need help with ACER?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.
About the developer
215 Stars 
39 Forks 
MIT License 
99 Commits 
0 Opened issues 
Description
Actor-critic with experience replay
Services available
Contributors list
Readme
ACER
Actor-critic with experience replay (ACER) [1]. Uses batch off-policy updates to improve stability. Trust region updates can be enabled with
--trust-region. Currently uses full trust region instead of "efficient" trust region (see issue #1).
Run with
python main.py. To run asynchronous advantage actor-critic (A3C) [2] (but with a Q-value head), use the
--on-policyoption.
Requirements
To install all dependencies with Anaconda run
conda env create -f environment.ymland use
source activate acerto activate the environment.
Results
Acknowledgements
References
[1] Sample Efficient Actor-Critic with Experience Replay
[2] Asynchronous Methods for Deep Reinforcement Learning