Simulation: Life as a Survival Optimization Problem

As someone who came to the Machine Learning world from a Medical background, I couldn’t help not relating being stuck at a Local Maximum to other life situations. So I have decided to make a simulation project that helps to visualize this problem from a biological and also a political perspective where liberals and conservatives…

Genetic Algorithm vs. Stochastic Gradient Descent

Genetic Algorithm (GA) and Stochastic Gradient Descent (SGD) are well-known optimization methods and are used for learning in Neural Networks. There are various implementations of GA, however, most of them (e.g. Neat) are not directly comparable to SGD because these GA methods use point/localized mutations in their connections/weights. Geoffrey Hinton, in one of his videos…