Becca is a general learning program for use in any robot or embodied system. When using Becca, a robot learns to do whatever it is rewarded to do, and continues learning throughout its lifetime.
conda update conda
conda update anaconda
pip install becca
becca_test installs automatically when you install becca.
python
>>>import becca_test.test
>>>becca_test.test.suite()
Some videos show Becca in action.
Becca aspires to be a brain for any robot, doing anything. It's not there yet, but it's getting closer.
It may be able to drive your robot. Hook it up and see, using the worlds in the becca_test repository
as a model. Feel free to shoot me an email (brohrer@gmail.com) if you'd like to talk it through.
I owe you this. It's on my To-Do list.
In the meantime, the reinforcement learner is similar to the one from Becca 7 (described in this video) and the unsupervised ziptie algorithm hasn't changed from Becca 6 (described on pages 3-6 of this pdf).
The code is also generously documented. I explain all my algorithmic tricks and justify some of my design decisions. I recommend starting at connector.py and walking
through from there.
The good folks at OpenAI have created a playground called Gym for Becca and agents like it. Learning on simulated robots of all types and complexities is a great opportunity to show what Becca can do. Getting Becca integrated with Gym is my next development goal. There are some intermediate steps, and I'll be working through them for the next several months.
