rl_roboschool_stable_baselines

Roboschool simulations training with stable baselines on Amazon SageMaker

Roboschool is an open source physics simulator that is commonly used to train RL policies for robotic systems. Roboschool defines a variety of Gym environments that correspond to different robotics problems. One of them is HalfCheetah which is a two-legged robot, restricted to a vertical plane, meaning it can only run forward or backward.

In this notebook example, we will make HalfCheetah learn to walk using the stable-baselines a set of improved implementations of Reinforcement Learning (RL) algorithms based on OpenAI Baselines.

Contents

• rl_roboschool_stable_baselines.ipynb: Notebook demonstrating the code to make HalfCheetah learn to walk.
• Dockerfile: Dockerfile building the container with Roboschool, OpenMPI, stable-baselines and their dependencies by using SageMaker's RL tensorflow container as base.
• src/
  • preset-half-cheetah.py: Preset for HalfCheetah distributed training with Stable-Baselines PPI1.
  • train_stable_baselines.py: Training Stable-Baselines launcher script.
• resources: Files required as part of docker build.
• examples:
  • robo_half_cheetah_10x_40min.mp4: Output RL video for model trained using the rl_roboschool_stable_baselines.ipynb notebook with 10 ml.c4.xlarge instances and num_timesteps as 1e7