Ftr, your example it's one of classification.
I'm on my phone, so you're going to do the googling. Search for support vector machines. These are among the best to perform classification jobs.
On the other hand, Artificial Neutral networks can reproduce anything they're trained to do... and can interpolate over their training set quite easily. So you don't need to train it with every outcome in mind, just general cases and the network gives a pretty good guess for the correct answer to a new case that can be a mix of the training cases.
I think the biological brain is an ever learning neutral network with a lot of classification mechanisms thrown in the mix.
A cool example of how good we are at classification is letters. You can identify the same letter for a multitude of fonts and handwriting.
I'm on my phone, so you're going to do the googling. Search for support vector machines. These are among the best to perform classification jobs.
On the other hand, Artificial Neutral networks can reproduce anything they're trained to do... and can interpolate over their training set quite easily. So you don't need to train it with every outcome in mind, just general cases and the network gives a pretty good guess for the correct answer to a new case that can be a mix of the training cases.
I think the biological brain is an ever learning neutral network with a lot of classification mechanisms thrown in the mix.
A cool example of how good we are at classification is letters. You can identify the same letter for a multitude of fonts and handwriting.
