Sensorimotor learning basic lib

A python library of code I use for sensorimotor learning experiments with simulations, robots, etc. The basic idea is to generate states (sensors) with actions (motors), learn different predictive models from that data to approximate the sensorimotor dynamics and use the models to compute future actions.

This repository is in an early stages of release which I push on the occasion of sharing the smp_sphero code ¹. Still performing incremental clean-up and refactoring plus additions from existing private repository.

New idea for structure:

• models: fit/predict (offline), fitpredict (online)
• sensorimotor loops
• data and logging

Dependencies

We have the standard main dependencies of numpy, scipy, matplotlib, and sklearn which are needed regardless. You can either install them via package manager

apt-get install python-numpy python-scipy python-matplotlib python-sklearn

Optional modules are rlspy (recursive least squares implementation) from ² and jpype ³, a java to python bridge which we use for computing information theoretic measures with the java information dynamics toolkit ⁴.

Additional dependencies which might be made optional in the future are pandas, ros, pyunicorn, and mdp/Oger.

apt-get install python-pandas python-mdp

For installing a basic ROS stack see the wiki at https://www.ros.org/wiki, you need to have the package python-rospy.

Pyunicorn does recurrence analysis and can be obtained from https://github.com/pik-copan/pyunicorn or via pip.

Oger is an extension for MDP and can be obtained from http://reservoir-computing.org/installing_oger.

Configuration

The path to certain libraries can be set in the config file. See config.py.dist for possible options.

Reservoir lib

reservoirs.py	contains Reservoir class, LearningRules class, a few utility functions and a main method
	that demonstrates basic use of the class. It can definitely be simplified (WiP)
learners.py	this model embeds the underlying adaptive model into the sensorimotor context
eligibility.py	basic eligibility windows used in a variant of learning rules
smp\\\_thread.py	thread wrapper that provides constant dt run loop and asynchronous sensor callbacks

You could try and run

python reservoirs.py

or

python reservoirs.py --help

to see possible options. Documentation and examples upcoming.

Footnotes

¹ https://github.com/x75/smp_sphero

² https://github.com/bluesquall/rlspy

³ Either python-jpype via apt, or from pip either jpypex or JPype1

⁴ https://github.com/jlizier/jidt