Decoding Motor Skills of Artificial Intelligence and Human Policies: A Study on Humanoid and Human Balance Control

Abstract

From the advancement in computers, computeraided design has emerged for mechanical and electronic engineering, architecture, and many other engineering fields. Foreseeing a similar development curve and technology wave, we forecast a new emerging discipline in the near future that uses learning-aided approaches to catalyze control development, alongside other similar applications such as medicine discovery. In this article, we propose a new paradigm for using machine learning to facilitate quicker, more efficient, and more effective control development, as an alternative way of leveraging the power of machine learning in addition to other options that intend to use learning directly in real-world applications.