Title: AlteregoNets: a way to human augmentation,
Abstract: A person dependent network, called an AlterEgo net, is proposed for
development. The networks are created per person. It receives at input an
object descriptions and outputs a simulation of the internal person's
representation of the objects. The network generates a textual stream
resembling the narrative stream of consciousness depicting multitudinous
thoughts and feelings related to a perceived object. In this way, the object is
described not by a 'static' set of its properties, like a dictionary, but by
the stream of words and word combinations referring to the object. The network
simulates a person's dialogue with a representation of the object. It is based
on an introduced algorithmic scheme, where perception is modeled by two
interacting iterative cycles, reminding one respectively the forward and
backward propagation executed at training convolution neural networks. The
'forward' iterations generate a stream representing the 'internal world' of a
human. The 'backward' iterations generate a stream representing an internal
representation of the object. People perceive the world differently. Tuning
AlterEgo nets to a specific person or group of persons, will allow simulation
of their thoughts and feelings. Thereby these nets is potentially a new human
augmentation technology for various applications.