Simulation and Evolution of Artificial Life

Ovaj rad opisuje simulaciju umjetnog života unutar dinamičnog ekosustava u kojemu se nalaze bića i hrana. Fokusira se na Darwinovske evolucijske dinamike i preživljavanje najjačeg, s idejom postepenog poboljšanja cijele vrste uzrokovanog evolucijskim pritiscima. Koristeći neuronske mreže za model mozga, bića su pokazala prilagodljivost, sposobnost za učenjem i fleksibilnost u snalaženju u neviđenim i nepredvidljivim situacijama. Procesom razmnožavanja i mutiranja, uz pomoć genetičkih algoritama, jedinke su naučile učinkovito se kretati svojom okolinom u potrazi za hranom i razmnožavati se mitozom, pritom uzimajući u obzir količinu vlastite energije. Simulacija je tako pokazala osnovne mehanizme napretka živih bića koji vjerodostojno reflektiraju kompleksne mehanizme stvarnog svijeta.This paper describes the simulation of artificial life within a dynamic ecosystem containing creatures and food. It focuses on Darwinian evolutionary dynamics and the survival of the fittest, with the idea of gradual improvement of the entire species caused by evolutionary pressures. Using neural networks to model the brain, the creatures showed adaptability, the capacity to learn and the flexibility to navigate in unprecedented and unpredictable situations. Through the process of reproduction and mutation, with the help of genetic algorithms, individuals have learned to efficiently move around their environment in search of food and reproduce by mitosis, while considering the amount of their own energy. The simulation thus showed the basic mechanisms of the progress of living beings that faithfully reflected the complex mechanisms of the real world