Stable Kernels and Fluid Body Envelopes

Abstract

Recent advances in robotics lead us to consider, on the one hand, the notion of a kernel, a set of stable algorithms that drive developmental dynamics and, on the other hand, variable body envelopes that change over time. This division reverses the classic notion of a fixed body on which different software can be applied to consider a fixed software that can be applied to different kinds of embodiment. We discuss the case of generic algorithms capable of learning to control a robotic body without knowing its characteristics beforehand. With such kind of algorithms you can perform experiences where you can precisely characterize the importance of the embodiment in the final behavior obtained, simply by changing the embodiment and keeping the software kernel stable. Thus, it becomes possible to study how a particular embodiment shapes developmental trajectories in specific ways. It also leads us to a new view of the development of skills, from sensorimotor dexterity to abstract thought, based on the notion of a fluid body in continuous redefinition.