Evolutionary Process

Evolutionary processes are being investigated through computational models to understand how biological systems adapt and optimize over time, focusing on the interplay between genotype and phenotype. Current research employs diverse approaches, including artificial neural networks, genetic algorithms, and cellular automata, to simulate evolution in various contexts, such as the development of multicellular organisms, the optimization of robot morphologies and controllers, and the improvement of machine learning algorithms. These studies offer insights into fundamental biological mechanisms and provide powerful tools for solving complex optimization problems in engineering and computer science.