From Fixed-Point Flows to Hysteresis Oscillators

Abstract

Homeokinesis realizes the self-organization of artificial brain-body systems by gradient descending the time-loop error, a quantity that is truly internal to the robot since it is defined exclusively in terms of its sensorimotor dynamics. Homeokinesis can therefore be considered as a self-supervised learning procedure with the special effect of making the brain-body system self-referential. We will study this phenomenon here in an idealized one-dimensional world in order to identify key features of our self-referential dynamical systems independently of any specific embodiment effects. In particular, we will gain some insight into the entanglement of state and parameter dynamics and investigate the way how the latter induces behavioral variability.