自学习系统中过程的可视化

G. Peters, K. Bunte, M. Strickert, Michael Biehl, T. Villmann
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引用次数: 3

摘要

自组织系统的一个方面是它们期望的自我学习能力,即能够动态地适应环境中的条件。这种质量是尴尬的,特别是当它涉及到安全或安全敏感领域的应用程序。在这方面,可以通过提供系统过程的透明度,向更可信的系统迈出一步。向操作员提供反馈的一个重要手段是系统内部过程的可视化。在这篇立场文件中,我们讨论了可视化动态过程的问题,特别是在自学习系统中。我们以计算机视觉领域的一个现有的自学习系统为例,从中我们得出了一些普遍感兴趣的问题,例如在动态学习系统中可视化信息流的可能选项或符号数据的可视化。作为一个副作用,学习过程的可视化可以提供对一般学习的基本原理的更好理解,也就是在生物系统中。这也可能有助于改进未来自主学习系统的设计。
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Visualization of processes in self-learning systems
One aspect of self-organizing systems is their desired ability to be self-learning, i.e., to be able to adapt dynamically to conditions in their environment. This quality is awkward especially if it comes to applications in security or safety-sensitive areas. Here a step towards more trustful systems could be taken by providing transparency of the processes of a system. An important means of giving feedback to an operator is the visualization of the internal processes of a system. In this position paper we address the problem of visualizing dynamic processes especially in self-learning systems. We take an existing self-learning system from the field of computer vision as an example from which we derive questions of general interest such as possible options to visualize the flow of information in a dynamic learning system or the visualization of symbolic data. As a side effect the visualization of learning processes may provide a better understanding of underlying principles of learning in general, i.e, also in biological systems. That may also facilitate improved designs of future self-learning systems.
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