README.md

Reproduce DDPG with PARL

Based on PARL, the DDPG algorithm of deep reinforcement learning has been reproduced, reaching the same level of indicators as the paper in Mujoco benchmarks.

Paper: DDPG in Continuous control with deep reinforcement learning

Mujoco games introduction

PARL currently supports the open-source version of Mujoco provided by DeepMind, so users do not need to download binaries of Mujoco as well as install mujoco-py and get license. For more details, please visit Mujoco.

Benchmark result

+ Each experiment was run three times with different seeds

How to use

Dependencies:

• python3.7+
• parl>=2.1.1
• paddlepaddle>=2.0.0
• gym>=0.26.0
• mujoco>=2.2.2

Start Training:

# To train an agent for HalfCheetah-v4 game
# python train.py

# To train for other game
# python train.py --env [ENV_NAME]