Flynn Andrew, Amann Andreas
School of Mathematical Sciences, University College Cork, Cork, Ireland.
INFANT Research Centre, University College Cork, Cork, Ireland.
Front Netw Physiol. 2024 Oct 3;4:1451812. doi: 10.3389/fnetp.2024.1451812. eCollection 2024.
The concept of multifunctionality has enabled reservoir computers (RCs), a type of dynamical system that is typically realized as an artificial neural network, to reconstruct multiple attractors simultaneously using the same set of trained weights. However, there are many additional phenomena that arise when training a RC to reconstruct more than one attractor. Previous studies have found that in certain cases, if the RC fails to reconstruct a coexistence of attractors, then it exhibits a form of metastability, whereby, without any external input, the state of the RC switches between different modes of behavior that resemble the properties of the attractors it failed to reconstruct. In this paper, we explore the origins of these switching dynamics in a paradigmatic setting via the "seeing double" problem.
多功能性的概念使得储层计算机（RCs），一种通常被实现为人工神经网络的动态系统，能够使用同一组训练权重同时重构多个吸引子。然而，在训练RC来重构多个吸引子时会出现许多其他现象。先前的研究发现，在某些情况下，如果RC未能重构吸引子的共存状态，那么它会表现出一种亚稳形式，即，在没有任何外部输入的情况下，RC的状态会在不同的行为模式之间切换，这些模式类似于它未能重构的吸引子的属性。在本文中，我们通过“看到双重”问题在一个典型场景中探究这些切换动力学的起源。
