These days, most neural network frameworks are essentially collections of functions on multidimensional arrays with added support for a particular type of automatic differentiation (backpropagation). These features are generally useful for any task that requires numerical optimization (deep learning happens to be one of them) and, in this article, I…

In this post I will explain the main idea behind the paper Average Vector Field Integration for St. Venant-Kirchhoff Deformable Models. I will try to give some context before explaining the main idea of the method in case you’re not too familiar with physics-based simulation. At the end of the…

Inspired by some artificial life papers, I implemented a genetic algorithm to evolve locomotion skills in virtual creatures with deformable bodies. Despite using a somewhat simple model, some interesting behaviors emerged. The body Many projects about simulated evolution of virtual creatures use rigid parts connected with joints for the creatures’ bodies…