Designing spontaneous behavioral switching via chaotic itinerancy

TL;DR

This paper presents a novel method to controllably induce and design chaotic itinerancy in high-dimensional systems, enabling autonomous behavioral switching in neurorobotics.

Contribution

It introduces a reproducible approach to implement and design chaotic itinerancy by adjusting system parameters in high-dimensional chaotic systems.

Findings

Method allows easy design of quasi-attractor trajectories.

Transition rules among attractors can be controlled.

Numerical experiments validate the approach.

Abstract

Chaotic itinerancy is a frequently observed phenomenon in high-dimensional and nonlinear dynamical systems, and it is characterized by the random transitions among multiple quasi-attractors. Several studies have revealed that chaotic itinerancy has been observed in brain activity, and it is considered to play a critical role in the spontaneous, stable behavior generation of animals. Thus, chaotic itinerancy is a topic of great interest, particularly for neurorobotics researchers who wish to understand and implement autonomous behavioral controls for agents. However, it is generally difficult to gain control over high-dimensional nonlinear dynamical systems. Hence, the implementation of chaotic itinerancy has mainly been accomplished heuristically. In this study, we propose a novel way of implementing chaotic itinerancy reproducibly and at will in a generic high-dimensional chaotic system. In particular, we demonstrate that our method enables us to easily design both the trajectories of quasi-attractors and the transition rules among them simply by adjusting the limited number of system parameters and by utilizing the intrinsic high-dimensional chaos. Finally, we quantitatively discuss the validity and scope of application through the results of several numerical experiments.