Last Thursday professor El-Ghazali Talbi from Lille University hold a talk about metaheuristic classification and his unified framework ParadisEO to deal with it on the Elx University Miguel Hernandez CIO, and after the talk (I enjoyed it a lot and learn things a was supposed to already know and some more!) I had a little time to explain my latest fractal methods and show some of the videos I had been producing about them.
There was some debate after the talks about the classification itself and the Pareto frontier way of working on multi objective optimisation problems.
Basically, actual approaches try to maximise all the functions at the same time, if possible, and if not, then obtain the optimum solution for any weighted combination of those functions, so for any possible combination you get a point, and all those points form the "Pareto Frontier" of the problem.
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.
Friday, 29 April 2016
Thursday, 28 April 2016
Understanding the mining example
My friend Samuel (@Samuel__GP) suggested me -in a comment- to try to explain how simple the idea used is compared with the rich an efficient behaviours it produces on the rocket, and it is not easy, but I will try...
So first have a look at this video:
The goal of the player is to pick up rocks with it's hook and then take them to the deploy area (the small circle filled with a grid). Once the rock is there, the hook releases and you can not trap the rock again until it leaves the big circle. In that moment, the rocket will try to catch it again and so on.
Monday, 18 April 2016
Entropic AI using Excel
Some days ago, Raul Perez (@raulperezrpm) kindly contacted me on twitter to comment about my first talk on entropic intelligence, and just two days later, I received a video from him of the entropic algorithm working inside Excel macros!
Saturday, 9 April 2016
Emotional links
Adaptive foraging, or the ability to harvest and collect items, is the main test-bed for swarm intelligences, as it resemble real life problems and mimic interesting social behaviours like ants and bees swarms.
So I am adapting my fractal AI code to deal with this problem, and as a first result, here I show you a video with only one agent (quite a small swarm!) so I can test if the new gadgets works OK.
The rocket now have a hook that will trap asteroids as a magnet. The hook is connected to the rocket with a rubber band, making the rocket-hook structure quite difficult to manage.
So I am adapting my fractal AI code to deal with this problem, and as a first result, here I show you a video with only one agent (quite a small swarm!) so I can test if the new gadgets works OK.
The rocket now have a hook that will trap asteroids as a magnet. The hook is connected to the rocket with a rubber band, making the rocket-hook structure quite difficult to manage.
Are maths the real languaje of nature?
I have just had a vision random thought I wanted to share before going to bed: What if mathematics were not the real basement of real world physics? What if the laws of nature are not really physicals laws written in pure maths as we all have naively assumed? Can physics be rethink in a absolutely different way?
I think there exists a way to describe all known physics without using any mathematical formula, a way to describe what a "wave equation" really is without using mathematically defined fields of any kind, just using algorithmics, in fact using just a single, small and compact algorithm.
I think there exists a way to describe all known physics without using any mathematical formula, a way to describe what a "wave equation" really is without using mathematically defined fields of any kind, just using algorithmics, in fact using just a single, small and compact algorithm.
Tuesday, 16 February 2016
Folding proteins with a fractal
Yesterday I posted about the fractal algorithm adapted to function optimising, the test I showed was nice, but dealing with a 2D function is not so great if you plan to go big.
After that Guillem forgot to go home and stayed coding a little more at the office. This morning the algorithm was able to load test proteins and try to fold them by minimising the Lennard-Jones potential of the cluster. He sleept in the sofa!
Here you see it folding a 5 atoms "protein":
After that Guillem forgot to go home and stayed coding a little more at the office. This morning the algorithm was able to load test proteins and try to fold them by minimising the Lennard-Jones potential of the cluster. He sleept in the sofa!
Here you see it folding a 5 atoms "protein":
Monday, 15 February 2016
Serious fractal optimizing
Guillem Duran, my friend and college from twitter, is now full-time at work with me at converting the "one way" fractal algorithm used in my latest AI into a "serious" general optimising algorithm in python: given a function, find its global (as opposed to local) maximum -or minimum- value it can get on its entire domain -the points on the state space where the function is defined.
Last week we finished the conversion, so we are just starting to benchmark it against other "state of the art" similar algorithms, but to have a first view of the you have a preliminar video here:
Last week we finished the conversion, so we are just starting to benchmark it against other "state of the art" similar algorithms, but to have a first view of the you have a preliminar video here:
Subscribe to:
Comments (Atom)