Using Assembler Encoding to Solve Inverted Pendulum Problem

Abstract

Assembler Encoding is Artificial Neural Network encoding method. To date, Assembler Encoding has been tested in two problems, i.e. in an optimization problem in which a solution is in the form of a matrix and in the so-called predator-prey problem in which the task of ANN is to control agent-predators whose common goal is to capture a fast moving agent-prey. The next problem in which Assembler Encoding was tested is the inverted pendulum problem. In the experiments Assembler Encoding was compared to several evolutionary and reinforcement learning methods. The results of the tests are presented at the end of the paper.