Muhtasham / ddpg-aigym

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

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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

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.

About

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

License:MIT License


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Language:Python 100.0%