README.md

Reproduce SAC with PARL

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

Include following approaches:

• DDPG Style with Stochastic Policy
• Maximum Entropy

SAC in Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Mujoco games introduction

Please see here to know more about Mujoco games.

Benchmark result

How to use

Dependencies:

• python3.5+
• paddlepaddle>=1.6.1
• parl
• gym
• mujoco-py>=1.50.1.0

Start Training:

# To train an agent for HalfCheetah-v2 game
python train.py

# To train for different games
# python train.py --env [ENV_NAME]