Emergence of diverse behaviors from interactions between nonlinear oscillator complex networks and a musculoskeletal system

Abstract

To understand the relationship between brain structure and behavior in the general movements of fetuses and infants from a complex systems perspective, we investigated how behaviors emerge from interactions between complex networks of nonlinear oscillators and musculoskeletal bodies. We prepared a snake-like robot and some network structures in a physical simulator. The various conditions imposed on the networks were (a) no connection among oscillators, (b) scalefree network, (c) one-dimensional lattice, (d) small-world network, and (e) random network. In the experiments, the robot exhibited multiple crawling and bending behaviors. By estimating the numbers of behavioral attractors, we revealed a qualitative difference between the scale-free network and other complex networks.