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Self-organization in a Simple Task of Motor Control Based on Spatial Encoding

机译：基于空间编码的电机控制简单任务中的自组织

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摘要

This paper elaborates on the possibilities for self-adjustment of a biological neural network used as feedback controller in the motor control system of a six-legged walker. As biological systems, in contrast to technical systems, show an impressive capability of self-adaptation, this is meant as a proof of principle. Complementing an intensity encoded system (Linder, 2002), where scalar values are represented as the activity of a given neuron, this mechanism is based on spatial encoding, where a scalar value is represented as the location of the most active neuron in a chain of neurons. This encoding scheme can often be observed in biological systems. While the intensity encoded system requires linear input characteristics and symmetrical distribution of the input values over the whole range for both target angles and actual angles, the spatially encoded system presented here is completely self-organizing for evenly distributed target angles and actual angles. By employing an internal teaching signal, it can even adjust for arbitrary (i.e., biologically relevant) distributions of the input. This internal signal is provided through body geometry. Instead of error back-propagation, the system exploits local neuronal mechanisms implicated by a biologically plausible realization of self-organizing maps.
机译：本文阐述了生物神经网络自我调节的可能性，该神经网络用作六足助行器的电机控制系统中的反馈控制器。与技术系统相比，生物系统显示出令人印象深刻的自适应能力，因此这是原理的证明。作为强度编码系统（Linder，2002）的补充，其中标量值表示为给定神经元的活动，此机制基于空间编码，其中标量值表示为一串神经元中最活跃的神经元的位置。神经元。通常可以在生物系统中观察到这种编码方案。虽然强度编码系统需要线性输入特性，并且输入值在目标角度和实际角度的整个范围内都呈对称分布，但此处介绍的空间编码系统对于目标角度和实际角度均匀分布是完全自组织的。通过使用内部示教信号，它甚至可以调整输入的任意（即生物学相关的）分布。该内部信号通过身体的几何形状提供。该系统利用错误的反向传播，而不是利用自组织图的生物学上合理的实现所牵涉的局部神经元机制。

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