Wednesday, November 9, 2011

Neural networks part 1: Teaching Canyonero to drive

Artificial neural networks (ANNs) are modeled after natural neural networks (brains and nervous systems) and though they don't work exactly alike, both a brain and an ANN can learn arbitrarily complex tasks without being told exactly how - they just need data about the task and their performance.

A generic artificial neural network.

ANNs have been applied to a lot of artificial intelligence and machine learning problems, from autonomous vehicle driving to recognizing handwritten address on envelopes to creating artificial intelligence for video game agents.
I won't go deep into the math behind ANNs here; there are great sites on the web (and it's not really difficult, there's just a lot of bookkeeping). 

Instead, I'll take two posts to describe a couple of neural net projects I've worked on. First up: a mobile robot called Canyonero that learned to compensate for its own mismatched wheels.

Canyonero, with a camera in the front and a netbook running an ANN.