Machine Learning

Training an inverted-pendulum stabilizing RNN by genetic algorithm

Inspired by a lecture about heuristic optimization I implemented various GA experiments in my go-to 3d package Houdini, where robust rigid-body simulations are possible. In this example I trained a recurrent neural network (RNN) to stabilize an inverted double pendulum. The loss function was integrating the distance to the target position over the course of a single episode. The complete RNN including activations (on shperes) and weights (on edges) is shown on the left, while on the right the current population can be seen, with the best performers closest to the camera.