Control of an inverted pendulum by a neural network with self-supervised learning

Abstract

Summary form only given, as follows. The authors propose an adaptive self-supervised learning system based on a neural network with supervised learning. The adaptive system learns the desired task autonomously. Although this system, like many adaptive learning systems, uses trial and error, experience rules are implemented into the system as an equation so that the system can effectively generate training data based on the experience rules during trial and error and train the neural network controlling the system itself via supervised learning. The authors discuss control of an inverted pendulum to show how the adaptive system is used. The system was able to invert the pendulum stably at the target position. >