A hierarchical attention-based neural network architecture, based on human brain guidance, for perception, conceptualisation, action and reasoning
We present a neural network software architecture, guided by that of the human and more generally primate brain, for the construction of an autonomous cognitive system (which we have named GNOSYS). GNOSYS is created so as to be able to attend to stimuli, to conceptualise them, to learn their predicted reward value and reason about them so as to attain those stimuli in the environment with greatest predicted value. We apply this software system to an embodied version in a robot, and describe the activities in the various component modules of GNOSYS, as well as the overall results. We briefly compare our system with some others proposed to have cognitive powers, and finish by discussion of future developments we propose for our system, as well as expanding on the arguments for and against our approach to creating such a software system.
kcl kings college london uk utub university of tubingen germany forth foundation for research & technology  hellas institute of computer science heraklion greece ugdist university of genoa zenon zenon co. ltd. athens fef frontal eye fields ifg inferior frontal gyrus teo posterior temporal lobe te temporal lobe lip lateral parietal lobe tpj tempero-parietal junction spl superior parietal lobe vta ventral tegmental area nacc nucleus accumbens ofc orbito-frontal cortex ctx cortex td temporal difference lgcu local cerebral glucose utilisation fm forward model imc inverse model controller