A deep learning technique to solve Rubik's cube and other problems step-by-step

Colin G. Johnson, an associate professor at the University of Nottingham, recently developed a deep-learning technique that can learn a so-called "fitness function" from a set of sample solutions to a problem. This technique, presented in a paper published in Wiley's Expert Systems journal, was initially trained to solve the Rubik's cube, the popular 3-D combination puzzle invented by Hungarian sculptor Ernő Rubik. "The aim of our paper was to use machine learning to learn to solve the Rubik's cube," Colin G. Johnson, one of the researchers who carried out the study, told TechXplore. "Rubik's cube is a very complex puzzle, but any of the vast number of combinations is at most 20 steps from a solution. So the approach we take here is to try and solve the problem by learning to do each of those steps individually."