Recurrent Deterministic Policy Gradient (RDPG)

Overview

PyTorch implementation of Recurrent Deterministic Policy Gradient from the paper Memory-based control with recurrent neural networks

Run

• Training:

  • Pendulum-v0

  $ python main.py --env Pendulum-v0 --max_episode_length 1000 --trajectory_length 10 --debug

• Testing (TODO)

References:

• Memory-based control with recurrent neural networks <https://arxiv.org/abs/1512.04455>
• Continuous control with deep reinforcement learning <https://arxiv.org/abs/1509.02971>
• DDPG implementation using PyTorch <https://github.com/ghliu/pytorch-ddpg>
• PyTorch-RL <https://github.com/jingweiz/pytorch-rl>