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Odysseus: DDPG with Hindsight Experience Replay

Abstract

This is a pytorch implementation of Hindsight Experience Replay.

Introduction

Installation

Linux: https://mpi4py.readthedocs.io/en/stable/install.html

https://neptune.ai/blog/installing-mujoco-to-work-with-openai-gym-environments

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/andreas/.mujoco/mjpro150/bin

sudo apt-get install libosmesa6-dev

sudo apt-get install patchelf

Usage

  1. train the FetchReach-v1:
mpirun -np 1 python main.py --env='FetchReach-v1' --clip-return --device='cuda' --debug-mode --name='FetchReach-v1' --auto-save --logger-name='FetchReach-v1' --checkpoint-dir '../../../../data/experiments'
  1. train the FetchPush-v1:
mpirun -np 8 python main.py --env='FetchPush-v1' --clip-return --device='cpu' --debug-mode --name='FetchPush-v1' --auto-save --logger-name='FetchPush-v1' --checkpoint-dir '../../../../data/experiments'
  1. train the FetchPickAndPlace-v1:
mpirun -np 16 python main.py --env='FetchPickAndPlace-v1' --clip-return --device='cpu' --debug-mode --name='FetchPickAndPlace-v1' --auto-save  --logger-name='FetchPickAndPlace-v1' --checkpoint-dir '../../../../data/experiments'
  1. train the FetchSlide-v1:
mpirun -np 1 python main.py --env='FetchSlide-v1' --clip-return --device='cuda' --debug-mode --name='FetchSlide-v1' --auto-save --logger-name='FetchSlide-v1' --checkpoint-dir '../../../../data/experiments'

Demo

Experiments

Table with pretrained model stats

Acknowledgement

Future Work

  • Add tensorboard
  • Add docstrings
  • Add instructions for mujoco on Windows
  • Experiments
  • Include pretrained models
  • Include examples
  • Complete README