-Neural Networks-
Neural networks are a simple way to give computers the ability to do complex tasks and seem to have 'intelligence.' These networks start out simply as dozens or perhaps hundreds of thousands of neurons each making its own decisions based on 'inputs.' Each neuron makes its decision based on one or several inputs. Each input will affect its decision with a weighting factor. These networks are usually taught their task using repetition after repetition. If the repetition affects the outcome in a negative or unwanted manner the last change will be undone and some other change tried. These changes are quite often random, that is why the number of repetitions is important as it sometimes can take a large number of changes to get any positive results out of a neural network. A lot of times if any more than a 10-20 neurons are in a network it will be quite difficult to figure out how a network is arriving at its results. The US Army recently tried using a neural network to recognize tanks hiding behind trees. They did this by showing it pictures after picture, some had tanks hiding behind trees and some didn't. The network eventually was able to tell which pictures had the tanks and which didn't. Unfortunately each picture with a tank in it was taken on a cloudy day. This network found it easier to find out which pictures had clouds in the sky instead of actually looking for tanks like the Army hoped. These are used pretty much everywhere today including trying to predict the stock market. These networks are often greeted with skepticism because large neural networks can be hard to predict and even harder to figure out how it arrives at a certain decision. This could be a prediction for airline stocks to go down after oil prices go up or perhaps it mistakenly based its decision based on "Home Depot's" stock.
Applets for Neural Networks and Artificial Life
Yahoo site with information on Neural nets and a good set of links
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