Ape-X DQN

This is TensorFlow implementation of Ape-X DQN : DISTRIBUTED PRIORITIZED EXPERIENCE REPLAY

In my code, multiprocessing is adopted to implement distribution of a learner and actors and multiprocessing.Queue is used to pass network parameters and trajectories among processes.

Environment : OpenAI Gym Atari 2600 games

Usage

$ python apex_dqn.py --num_actors 3 --env_name Alien-v0 --replay_memory_size 200000

All arguments are described in apex_dqn.py

Results

After 10,000 episodes (8 actors)

Learning curves