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common
examples
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src
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README.md
rl_roboschool_stable_baselines.ipynb

README.md

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