EA_Proyect

The project is divided into the following parts:

evolutionary-algortihms-report-template.pdf: A study where the basic concepts of evolutionary algorithms, its main operators, recent studies and different specifications of it, application areas, and the implementation of the “GA_Multi.py” module based on “GA.py” with multiprocessing are discussed.

- AI_Proyect_First_Approach.ipynb: First contact implementing a genetic algorithm for image reconstruction by generating random populations of figures. Each of the parts that compose the algorithm are detailed in this notebook, step by step

- GA: Folder where the two implementations of an improved genetic algorithm for the recreation of the image of the Gioconda are stored. On the one hand, we will have the file “Individual.py” referring to the individuals of the population, on the other hand “GA.py” as the base algorithm in which the generations are created.Finally, a last improvement with the file “GA_multi.py” where the generation of new populations is paralyzed by means of the division of the problem in smaller pieces of the same size, with the intention of trying that the software is able to reach better results in less time.