Python Library for Autonomous Exploration
Project description
# Explauto: A library to study, model and simulate curiosity-driven learning and exploration in virtual and robotic agents #
Explauto is a framework developed in the [Inria FLOWERS](https://flowers.inria.fr/) research team which provide a common interface for the implementation of active sensorimotor learning algorithm.
Explauto provides a high-level API for an easy definition of:
Virtual and robotics setups (Environment level)
Sensorimotor learning iterative models (Sensorimotor level)
Active choice of sensorimotor experiments (Interest level)
It is crossed-platform and has been tested on Linux, Windows and Mac OS. Do not hesitate to contact us if you want to get involved!
## Documentation ##
### Scientific grounding ###
Explauto’s scientific roots trace back from Intelligent Adaptive Curiosity algorithmic architecture [[Oudeyer 07]](http://hal.inria.fr/hal-00793610/en), which has been extended to a more general family of autonomous exploration architecture by [(Baranes, 2013)](http://www.pyoudeyer.com/ActiveGoalExploration-RAS-2013.pdf) and recently expressed as a compact and unified formalism [(Moulin-Frier, 2013)](http://hal.inria.fr/hal-00860641). We strongly recommend to read this [short introduction](http://flowersteam.github.io/explauto/about.html) into developmental robotics before going through the tutorials.
### Tutorials ###
[Setting a basic experiment](http://nbviewer.ipython.org/github/flowersteam/explauto/blob/master/notebook/01%20Running%20a%20basic%20experiment..ipynb)
[Comparing motor vs goal strategies](http://nbviewer.ipython.org/github/flowersteam/explauto/blob/master/notebook/02%20Comparing%20motor%20vs%20goal%20strategies.ipynb)
[Running pool of experiments](http://nbviewer.ipython.org/github/flowersteam/explauto/blob/master/notebook/03%20Running%20pool%20of%20experiments.ipynb)
[Introducing curiosity-driven exploration](http://nbviewer.ipython.org/github/flowersteam/explauto/blob/master/notebook/04%20Introducing%20curiosity-driven%20learning.ipynb)
[Poppy environment](http://nbviewer.ipython.org/github/flowersteam/explauto/blob/master/notebook/05%20%20Poppy%20environment.ipynb)
### API ###
The Explauto documentation on a html format can be found [here](http://flowersteam.github.io/explauto/).
## Installation ##
Explauto is available via pip. It can thus be installed with the classical:
pip install explauto
or:
easy_install explauto
The core of explauto depends of the following packages:
[python](http://www.python.org) 2.7 or 3.*
[numpy](http://www.numpy.org)
[scipy](http://www.scipy.org)
[scikit-learn](http://scikit-learn.org/)
[pandas](http://pandas.pydata.org)
For more details, please refer to the [installation section](http://flowersteam.github.io/explauto/installation.html) of the documentation.
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