Intuitive Physics with Crane Games

Abstract

With deep learning, the acquisition of eyes for artificial intelligence machines an allow the machines to understand physical concepts. Today's reserch on intuitive physics has approach three sorts of subject while in divided: the recognition of an object's physical properties, the understanding of physical laws, and action generation based on physical inference. However, even if all of these subjects are integrated, it only reach the level of several months after birth, and it is far from an understanding of Newton's law. In response, we propose a virtual crane game as a platform for computational model research on the development of physical intuition at the sensorimotor stage. By trying to solve this game by a simple learning agent, we discuss future research issues on this game.