Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
EPI
 
 
 
 
 
 
 
 
 
 

Environment Probing Interaction Policies

This repository contains the implementation for Environment Probing Interaction Policies.

Setup

Follow instructions to create a conda environment rllab3 with OpenAI Gym and Mujoco v1.31.

Usage

Training

source activate rllab3

# (Optional) Collect initial dataset for the prediction models. 
# Note that this step is optional since the dataset files are provided under EPI/envs/.
cd collect_initial_data
python collect_data_vine_hopper_8d.py
python collect_data_vine_striker.py

# Train Interaction Policy
cd ..
python train_interaction.py HopperInteraction -e 8
python train_interaction.py StrikerInteraction -e 8

# Train Task Policy
python train.py HopperTaskReset --epi_folder data/Exp190211_HopperInteraction_0/ --epi_itr 100 --params 8
python train.py StrikerTaskReset --epi_folder data/Exp180921_StrikerInteraction_3/ --epi_itr 200

#  Train Average Baseline or Oracle
python train.py HopperAvg
python train.py HopperOracle

Evaluation

 python evaluate.py data/Hopper/HopperTaskReset_0730/Exp180730_HopperTaskReset_6 --epi_folder data/Hopper/HopperInteraction_8/Exp180727_HopperInteraction_0/ --epi_itr 200

About

Code for Environment Probing Interaction Policies [ICLR 2019]

Topics

Resources

License

Releases

No releases published

Packages

No packages published

Languages