We've talked about that already **the cube of rubik**, it's a fascination for mathematicians, for their complexity, for the ability to study this kind of three-dimensional hobby.

Mathematicians have already shown the properties of the cube, the complexity and the way they are solved. The interesting thing, however, is that you**A neural network has learned to solve the cube **by himself.

## Technology challenge

Researchers from California University, Irving, have made an intelligent system that can, on average, resolve the cube, **in 1.2 seconds and use about 20 movements.**

This is **2 seconds faster than man holding the world record, with 3.47 seconds. **It can be said that normal people can solve it, know the basic algorithms, in about 50 seconds.

But the neural network, called **DeepCubeA, **It doesn't have the world record in & # 39; the resolution of & # 39; a cube between machines.

Other researchers showed up last year** a robot that could solve the cube in 0.38 seconds, **using the algorithm** ****min2phase****, **from MIT, that's just three times the algorithm used by the neural network.

## DeepCubeA learned through himself

While other algorithms were specifically designed to solve the cube, **DeepCubeA had to work out its own solution,** Your own way.

More interesting is the fact that **the researchers are not exactly sure **how DeepCubeA realized how to make it a color on each of & # 39; s faces.

Over there **several million possible combinations** for the cube, but only a complete state.

And while the researchers told him what the definitive state of the cube was, **DeepCubeA found for itself how to reach this solution** and today it is not fully understood how to develop its strategy.

One of the reasons for this may be** a neural network is finally a mathematical model, **symbolic, that is expressed by comparison. Moving from there to the conceptual part now seems to be a problem in neural networks.

## Personal training

The researchers, **for this study**, she started with a simulated version of Rubik's cube and stirred it.

**DeepCubeA trained him,** feed it** It took two days**s, improve their skills in an attempt to solve the most difficult combinations.

According to an article published in * Nature*, the researchers gave DeepCubeA

**10 million combinations and asked him to fix it in 30 than fewer moves.**

De** IA was tested with about a thousand combinations.** The system succeeded every time in solving the cube and did so in the minimum stipulated number of moves in 60% of & # 39; e try.

The algorithm can solve other games like the one **"Game of 15" and Sokoban.**

DeepCubeA uses an artificial neural network that emulates what human neurons do, with teaching techniques, where **To detect and teach learned patterns with input given by humans. **

It assumed an enhanced learning mechanism, which means that** what i learned was raising the state of problems** from a target state without having any knowledge about the domain.

Researchers **They had previously published an article** with another hobby approach, called *Approximate interaction policy*.

It has to be noticed **DeepCubeA's neural network was not specifically designed to solve Rubik's cubes, **The algorithm has broad implications:

"How can we create advanced AI that is more robust and capable of reasoning, understanding and planning?" Pierre Baldi, professor of computer science and senior author of the study, said: "This work is a step towards this much more complex goal".