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Designing spontaneous behavioral switching via chaotic itinerancy

机译:通过Chaotic Itinerancy设计自发行为切换

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Chaotic itinerancy is a frequently observed phenomenon in high-dimensional nonlinear dynamical systems and is characterized by itinerant transitions among multiple quasi-attractors. Several studies have pointed out that high-dimensional activity in animal brains can be observed to exhibit chaotic itinerancy, which is considered to play a critical role in the spontaneous behavior generation of animals. Thus, how to design desired chaotic itinerancy is a topic of great interest, particularly for neurorobotics researchers who wish to understand and implement autonomous behavioral controls. However, it is generally difficult to gain control over high-dimensional nonlinear dynamical systems. In this study, we propose a method for implementing chaotic itinerancy reproducibly in a high-dimensional chaotic neural network. 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 using the intrinsic high-dimensional chaos.
机译:混沌盈利是高维非线性动力系统中经常观察到的现象,其特征在于多个准吸引物之间的过渡过渡。几项研究指出,可以观察到动物脑中的高尺寸活性表现出混沌盈利,这被认为在自发行为生成中发挥着关键作用。因此,如何设计所需的混乱行程是一种令人兴趣的主题,特别是对于希望理解和实施自主行为控制的神经毒物研究人员。然而,通常难以获得对高维非线性动力系统的控制。在本研究中,我们提出了一种在高维混沌神经网络中可重复地在高维混沌神经网络中进行混沌潮流的方法。我们证明我们的方法使我们能够简单地通过调整有限数量的系统参数以及使用内在高维混沌来轻松地设计准吸引子的轨迹和它们之间的转换规则。

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