Thursday, 29 October 2015

Time traveling fractal AI, a first approach

Finding a way for the fractal futures to be able to travel back in time, as in Feynman diagrams and integrals, has proved to be a little tricky, but I feel I am quite near to solve it.

In the mean time, I want to share a "dead end" try to accomplish this by using succesive layers of futures sended to the future in different succesive times, so they act as a serie of concentric wave fronts that travels to the future reinforcing each other.

Let start by showing a nice video of this idea at work:

Friday, 9 October 2015

Maze: Fractal vs Entropic

Just after reading my own last post I wondered why I didn't let both algorithms to solve the maze in similar conditions so I could have a clear idea of how better one is compared to the older.

Wow, I didn't remebered the lineal "Entropic" AI to be so limited! I always tested it in the open field as I knew it didn't perform well in maze-like environments, but it looks like the google car racing against a F1.

So just have a look to the fractal "One Way" version of the last post solving the maze:

The One Way Fractal AI

Today I consider the "One Way" version of the fractal AI to be officially finished: I can not do it any better!

I have recorded a short video directly from my screen so you can watch it at work in slow motion, generated in real time in a very slow PC (no GPU, no cuda, no paralellization, no optimising, just old and dirty standard code) so you can watch the fractal as it grows up.

What you will see in the video are the "tips" of the branches of the fractal as it evolves in time (visit the post about "Fractal algorithm basics" for more info about what those "branches" are), like a "front wave" of imaginary futures scanning all the possibilities in front of you.

It really acts as a flock of silly birds, but a very special one: all the birds are totally blind, they change direction and velocity totally randomly, like having a crazy monkey pushing the joysticks randomly, but when one bird crashes, it is cloned to a safer position, the position of one of the "best birds" in the actual flock. This process of cloning and collapsing is what defines the "Fractal growth" as commented in the last post, and it makes it possible for the futures to reach the exit of a complicated maze quite automagically.

The video start by showing you the final fractal paths used to solve the maze, then I switched the app into "Slow motion debug" mode and made a new step of the thinking process, so you can see the fractal forming. The params were 1000 futures and 100 seconds.