Designing spontaneous behavioral switching via chaotic itinerancy

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.

15 pages, 6 figures and 1 supplementary figure. Our supplementary videos are available in https://drive.google.com/drive/folders/10iB23OMHQfFIRejZstoXMJRpnpm3-3H5?usp=sharing

References in corpus (3)

• Physical reservoir computing -- An introductory perspective
• Synchronization and chaos in a spin-torque oscillator with a perpendicularly magnetized free layer
• Chaos in nanomagnet via feedback current

Cited by in corpus (6)

• Embedding bifurcations into pneumatic artificial muscle
• Transient Chaos in BERT
• Composite FORCE learning of chaotic echo state networks for time-series prediction
• A Unifying Framework for Information Processing in Stochastically Driven Dynamical Systems
• Attractor-merging Crises and Intermittency in Reservoir Computing
• A Predictive Coding Account for Chaotic Itinerancy