life's complex processes. It can face incompleteness, and most importantly ignorance of data in a process model, contrarily to Artificial Intelligence, which requires exact knowledge. This technique tends to apply to a wide range of domains such as control, image processing and decision making. But it is also well introduced in the field of household appliances with washing machines, microwave ovens, etc. We can face it too when using a video camera, where it helps stabilizing the image while holding the camera unsteadily. Other areas such as medical diagnostics, foreign exchange trading and business strategy selection are apart from this principle's numbers of applications. Fuzzy logic is mainly useful for approximate reasoning, and doesn't have learning abilities, a qualification much needed that human beings have. It enables them to improve themselves by learning from their previous mistakes. Neural networks This is why CI experts work on the development of artificial neural networks based on the biological ones, which can be defined by 3 main components: the cell-body which processes the information, the axon, which is a device enabling the signal conducting, and the synapse, which controls signals. Therefore, artificial neural networks are doted of distributed information processing systems, enabling the process and the learning from experiential data. Working like human beings, fault tolerance is also one of the main assets of this principle. Concerning its applications, neural networks can be classified into five groups: data analysis and classification, associative memory, clustering generation of patterns and control. Generally, this method aims to analyze and classify medical data, proceed to face and fraud detection, and most importantly deal with nonlinearities of a system in order to control it. Furthermore, neural networks techniques share with the fuzzy logic ones the advantage of enabling data clustering. Evolutionary computation Based on the process of natural selection firstly introduced by Charles Robert Darwin, the evolutionary computation consists in capitalizing on the strength of natural evolution to bring up new artificial evolutionary methodologies. It also includes other areas such as evolution strategy, and evolutionary algorithms which are seen as problem solvers... This principle's main applications cover areas such as optimization and multi-objective optimization, to which traditional mathematical one techniques aren't enough anymore to apply to a wide range of problems such as DNA Analysis, scheduling problems... Learning theory Still looking for a way of "reasoning" close to the humans' one, learning theory is one of the main