Based on PARL, the TD3 algorithm of deep reinforcement learning has been reproduced, reaching the same level of indicators as the paper in Mujoco benchmarks.
Include following improvements:
- Clipped Double Q-learning
- Target Networks and Delayed Policy Update
- Target Policy Smoothing Regularization
TD3 in Addressing Function Approximation Error in Actor-Critic Methods
Please view here to know more about Mujoco games.
+ Each experiment was run three times with different seeds- python3.5+
- parl>=2.0.0
- paddlepaddle>=2.0.0
- gym==0.9.1
- mujoco-py==0.5.7
# To train an agent for HalfCheetah-v1 game
python train.py
# To train for different game
python train.py --env [ENV_NAME]