Attention, Learning, and the Value of Information

Despite many studies on selective attention, fundamental questions remain about its nature and neural mechanisms. Here I draw from the animal and machine learning fields that describe attention as a mechanism for active learning and uncertainty reduction and explore the implications of this view for understanding visual attention and eye movement control. I propose that a closer integration of these different views has the potential greatly to expand our understanding of oculomotor control and our ability to use this system as a window into high level but poorly understood cognitive functions, including the capacity for curiosity and exploration and for inferring internal models of the external world.

The Internet global network is a phenomenon of technological civilization, and its exceptional complexity surpasses anything mankind has ever created. In essence, what we are dealing with here is a huge quantity of utterly unstructured information. The Internet map is an attempt to look into the hidden structure of the network, fathom its colossal scale, and examine that which is impossible to understand from the bare figures of statistics.