Hello AI folks,
My name is Eric and I'm a student in Engineering physics in Lund, Sweden. I am very interested in machine learning and I've just started learning about how these things work. I’ve come to some realizations, so far I've understood that when you want to teach a coded program something either you have
1. A data set with input data and result which you run through your program to train it. For example the MNIST Data
http://yann.lecun.com/exdb/mnist/base2. You generate your own data and result by having a simulation environment. Just like the examples we've seen when a program learns how to play a video game.
After realising these two types of ways to train for example a neural network I started to wonder if you could do it differently. I started thinking about a couple of things.
1. Bringing the learning process into the real world, could there be factors that help the learning or would it just be, like in many other experiments, a too complex enviromen with too much data to handle for the learning program.
2. Could we compensate this environment with supervised learning? Could this affect the quality of the input data?
My idea:
Have a robot like the the Robotis OP2
http://en.robotis.com/index/product.php?cate_code=111310as an agent acting in my home. The inputs will be all the sensoric data it can detect and all it’s movements in form of walking, falling, getting up and so on. As far as I’ve understood I would need something like a cost-function, giving it a rating of how well it has achieved.
I’m thinking of trying to model its neural network to get as close as possible to an infants mind, being entirely impulsdriven (like babies are in their early years). That would mean that it’s objective would change all the time and therefore also the costfunction(?) which would decide the weights of each neuron, right?
I understand this sounds like an extremely difficult task but do you have any inputs with your knowledge of how machine learning actually works?
I’m trying to aim for a more flexible but initially simple system that can modify itself to a greater extent.
Thanks for all the help!