So called "Intelligente behaviour" can be defined in a pure thermodinamic languaje, using just "entropy". Formulaes look pretty intimidating, but once you get the idea, coding it into a working AI is quite simple.
Fractalizing the same idea takes away entropy calc form the AI and makes it work much better.
Before this blog I used to publish videos on a Youtube playlist about how the AI was better on this or that, it gave me a way to get comments on the subject.
Now that the blog is up and working, I would like to start by reviewing all those "old videos" and give an explanation on how the algorithm was working by this time, how good it was and witch things needed to be changed.
So today we will comment on the first video, it is the most important one to understand in order to get the whole idea of the algorithm, so read carefully and comment on any aspect you feel is not cleared in this post, I will try to help my best.
It chatched my attention so I jumped from link to link to link in search of some more insight on it. Reading those links made me understand the idea even before taking a look at the original paper, and when I read the world "Montecarlo", the algorithm popped up in my mind.
So I sat and code a quick and dirty approach to the algoritm in a couple of days, resulting in the first version of the kart simulator. It was very very simple, but the AI managed to drive the kart on track quite impresivley... and I didn't code anythink like "run" or "drive inside the track".
