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A Biologically Inspired Spatial Computer That Learns to See and Act

机译:一个生物学启发的空间计算机,了解和行动

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Vision and motor control are usually studied as separate phenomenon. They perform very different functions, they are performed by different regions of the brain, and one is perception while the other is actuation. The two structures did, however, co-evolve. While they are different structures they work together in reasoning about and manipulating the outside world. Both structures have some similar attributes. For example both the motor cortex and the visual cortex are laid out in a manner that preserves topological adjacency and the hippocampus, where positional awareness is represented also represents places in the world through a topological map. In all case the layout of the areas suggests algorithms that depend upon propagation through a kind of spatial computer in order to solve navigational tasks that combine perception, actuation, and spatial awareness. In this paper we take the position that it makes sense to study the computational aspects of learning to perform such tasks together rather than as separate disciplines and that by observing the similarities of the layouts of the associated areas we can gain some insight into a general learning engine that utilizes spatial computing principles in order to achieve complex behaviors in a complex world that can only be modeled imprecisely. This paper describes such an approach embedded within simple robotic devices.
机译:视觉和电机控制通常作为单独的现象进行研究。它们执行非常不同的功能,它们由大脑的不同区域执行,并且一个是感知而另一个是致动。然而,两种结构是合作的。虽然它们是不同的结构,但它们在推理和操纵外界的推理中一起工作。这两个结构都有一些类似的属性。例如,均以保留拓扑邻接和海马的方式布置电机皮质和视觉皮质,其中定位意识所代表的位置也代表世界中的地位通过拓扑图。在所有情况下,该区域的布局建议算法取决于通过一种空间计算机传播,以解决与感知,致动和空间意识相结合的导航任务。在本文中,我们采取了学习学习的计算方面的位置,而不是作为单独的学科来实现这些任务,并且通过观察相关领域的布局的相似之处,我们可以获得一些洞察一般学习的洞察力利用空间计算原则的发动机为了在复杂的世界中实现复杂行为,这些行为只能被不切实际地建模。本文介绍了在简单机器人设备中嵌入的这种方法。

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