FUNDAMENTALS OF GAME DESIGN, SECOND EDITION
Neural Nets
A neural net is a program that simulates, in a simplified form, the behavior of brain cells, or neurons. The details are too complex to discuss here, but put simply, a neural net mimics the brain's ability to recognize and correctly identify patterns of data. This is how we learn to tell an apple from an orange, for example: Our brains learn the visual patterns that apples and oranges fall into. Like the brain, a neural network has to be taught to recognize the pattern; after that, and with repeated exposure, the brain or the neural network identifies the pattern correctly.
Some efforts have been made to teach neural nets to learn to play strategy games by recognizing patterns of play that lead to success. Although this technique is worthy of further research, you shouldn't count on it. Neural nets take a long time to learn, and the process doesn't work well for complex patterns of information, such as the
dozens of possible choices available to a player in a modern war game. Furthermore, because of the way neural networks store data, there is no way to tell what the data actually mean. You can't teach the network a new pattern simply by tweaking the numbers stored inside it; you have to start over again from the beginning.
