One of the goals in this project is to facilitate the understanding about one of the many fields in the artificial intelligence, genetic algorithms. The way to achieve this goal has been through the visual representation of both execution and data.
In order to achieve this visual representation, the problem about teaching how to walk to a bipedal structure with the aforementioned genetic algorithms has been raised. First, an exhaustive investigation of the use of these algorithms has been carried out and similar projects made with them have been presented.
A graphic and physic engine have been necessary in order to be able to visualize the evolution and results. One of the best ways to understand the behaviour of something is beeing able to apply changes and study every parameter, by that, this tool develops counts with multitude of parametrization relative to the genetic algorithm behaviour.
Finally, this tool has been used to extract and detail the final results, that is, the solution to the given problem and the study of every parameter involved in the execution of the algorithm. This way, the user counts with the final results aswell as the posibility of using the tool to extract his own conclusions since the best way to learn something is by doing by yourself.
The source code is avaliable in the github repository and the full thesis aswell.
This project is awarded with honors as my final thesis for my degree in Multimedia Engineering.