This is the official code of our paper "Diversity-based Trajectory and Goal Selection with Hindsight Experience Relay" (PRICAI 2021)

Overview

Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay

This is the official implementation of our paper "Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay" (PRICAI 2021).

envs

Pre-requisites

  • python==3.6.8
  • gym==0.12.5
  • mujoco-py==2.0.2.0
  • tensorflow==1.13.1

Installation

  1. Install the OpenMPI:
sudo apt-get install openmpi-bin openmpi-doc libopenmpi-dev
  1. Install the required python packages.
  2. Install baseline:
pip install -e .

Usage

Enter to the specific location:

cd ./baselines/her/experiment

The scripts for FetchEnv:

python train.py --env_name FetchPush-v1 --clip_div=0.001 --use_kdpp True --prioritization diversity --seed 0 --n_epochs 50 --num_cpu 16 --logdir logs/fetchpushv1/cpu16ep50/alg=DDPG+DTGSH=/r0 --logging True
python train.py --env_name FetchPickAndPlace-v1 --clip_div=0.001 --use_kdpp True --prioritization diversity --seed 0 --n_epochs 50 --num_cpu 16 --logdir logs/fetchpickv1/cpu16ep50/alg=DDPG+DTGSH=/r0 --logging True

The scripts for HandEnv:

python train.py --env_name HandManipulateEggFull-v0 --use_kdpp True  --prioritization diversity --seed 0 --goal_type full --sigma 0.1 --n_epochs 50 --num_cpu 16 --logdir logs/handegg1/cpu16ep50/alg=DDPG+DTGSH=/r0 --logging True
python train.py --env_name HandManipulateBlockRotateXYZ-v0 --use_kdpp True  --prioritization diversity --seed 0 --goal_type rotate --sigma 0.1 --n_epochs 50 --num_cpu 16 --logdir logs/handblock1/cpu16ep50/alg=DDPG+DTGSH=/r0 --logging True
python train.py --env_name HandManipulatePenRotate-v0 --use_kdpp True --prioritization diversity --seed 0 --goal_type rotate --sigma 0.1 --n_epochs 50 --num_cpu 16 --logdir logs/handpen1/cpu16ep50/alg=DDPG+DTGSH=/r0 --logging True

Acknowledgements

Owner
Tianhong Dai
Deep Reinforcement Learning and Computer Vision
Tianhong Dai
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