Skip to content
Branch: master
Go to file
Clone

Latest commit

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
bin
 
 
cfg
 
 
doc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

grl

Build Status

Generic Reinforcement Learning Library

Copyright 2015-2019 Wouter Caarls

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Introduction

GRL is a C++ reinforcement learning library that aims to easily allow evaluating different algorithms through a declarative configuration interface.

Configurator

Installation (Ubuntu 16.04)

sudo apt-get install git cmake g++ libeigen3-dev
git clone https://github.com/wcaarls/grl.git

For the visualization, additionally install

sudo apt-get install libgl1-mesa-dev freeglut3-dev libz-dev

For the odesim environment, additionally install

sudo apt-get install libqt4-opengl-dev libtinyxml-dev libmuparser-dev libode-dev

For the RBDL environment and MUSCOD integration, additionally install

sudo apt-get install liblua5.1-dev

For the configurator, additionally install

sudo apt-get install python-yaml python-tk

For the zeromq addon, additionally install

sudo apt-get install libprotoc-dev protobuf-compiler libsodium-dev

Then download a recent (> 4.0.0) version of zeromq and run './configure, make, make install'

For the tensorflow addon, additionall install

sudo apt-get install libprotoc-dev protobuf-compiler

Then download TensorFlow for C from https://www.tensorflow.org/install/install_c in a place that can be found by the compiler and runtime environment.

Setup

mkdir build
cd build
cmake ..
make

Running

To directly perform an experiment, run

./grld ../cfg/pendulum/sarsa_tc.yaml

To start the configurator instead, run

cd ../bin
./grlc ../cfg/pendulum/sarsa_tc.yaml

Visualizations

GRL comes with standard visualizations for value functions, policies, and the integrated environments (e.g. pendulum swing-up, cart-pole swing-up, compass walker)

Visualizations

Further reading

See grl.pdf

You can’t perform that action at this time.