APEX DDPG Distributed Prioritized Experience Replay is an algorithm that decouples active learning from sampling. Actors interact with their own instances of the environment by selecting actions according to a shared neural network, and accumulate the resulting experience in a shared experience replay memory; the learner replays samples of experience and updates the neural network. The architecture relies on prioritized experience replay to focus only on the most significant data generated by the actors.
conda create -n rllib-apex-ddpg python=3.10
conda activate rllib-apex-ddpg
pip install -r requirements.txt
pip install -e '.[development]'