During these last years, I spent lot of time studying and working on artificial intelligence and artificial life. I also worked in several projects involving AI/AL derivated technologies like Bayesian network, (recurrent) neural network or genetic algorithms.

I first got fascinated about how some algorithm try to mimic our biological reality. Following the theoretical assumption "Hey! Why is this damn computers do not solve problems the way we do?", some friends and I tried to implement and integrate AI and AL knowledge into our projects.

Distinguishing intelligent systems from others is not a so trivial task. One primary ability of an intelligent system is when it is able to take a decision. But nowadays all computers make decisions all day and nights about which packets have to be forwarded, should the train make an emergency break, etc, etc without being considered as intelligent. So the point is that the system should take its decision by itself, without that any human has explicitly programmed it to do so. Typically, the system is trained with similar examples, and should be able to handle new decision based on its acquired knowledge. It is so called self-learning systems which are perhaps not sooo intelligent, but actually look the most like it (perhaps are human and mammals no more that such systems?).