shareeff / ddpg-aigym

Continuous control with deep reinforcement learning - Deep Deterministic Policy Gradient (DDPG) algorithm implemented in OpenAI Gym environments

ddpg-aigym

Deep Deterministic Policy Gradient

Implementation of Deep Deterministic Policy Gradiet Algorithm (Lillicrap et al.arXiv:1509.02971.) in Tensorflow

How to use

git clone https://github.com/stevenpjg/ddpg-aigym.git
cd ddpg-aigym
python main.py

During training

Once trained

Learning Curve

The learning curve for InvertedPendulum-v1 environment.

Dependencies

• Tensorflow
• OpenAi gym
• Mujoco

Features

• Batch Normalization (improvement in learning speed)
• Grad-inverter (given in arXiv: arXiv:1511.04143)

Note

To use different environment

experiment= 'InvertedPendulum-v1' #specify environments here

To use batch normalization

is_batch_norm = True #batch normalization switch

Let me know if there are any issues and clarifications regarding hyperparameter tuning.