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Kaixhin
224 Stars 41 Forks MIT License 99 Commits 0 Opened issues

Description

Actor-critic with experience replay

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ACER

MIT License

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-policy
option.

Requirements

To install all dependencies with Anaconda run

conda env create -f environment.yml
and use
source activate acer
to activate the environment.

Results

ACER

Acknowledgements

References

[1] Sample Efficient Actor-Critic with Experience Replay
[2] Asynchronous Methods for Deep Reinforcement Learning

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