In this chapter, we developed a generic MLP module, using formalized interfaces:
We designed an animat capable of gathering information from the environment to extract facts about its rocket shots. This enabled us to learn to predict the damage of each rocket. The animat can therefore select random targets, and use the perceptron to estimate the best:
Thanks to the perceptron, the AI developer spends less time solving a relatively complex problem. The perceptron exploits learning technology to improve the aiming capabilities beyond hand-crafted solutions. The MPL has the advantage of being easily adapted to the skills of different animats, too.
The next chapter presents an important concept: understanding the problem. This is an essential skill for AI developers because understanding the problem always drives AI system design.