----- Original Message ----- From: "Ben Goertzel" <[EMAIL PROTECTED]>
>snipped< The Novamente approach involves learning representations of objects learning a combination of supervised and unsupervised learning. E.g. from seeing a lot of TV's in different situations, and used in different contexts, the system will learn a whole bunch of overlapping probabilistic rules for recognizing TV's. So far we have not tested this process on real object perceived thru real cameras though -- just on simple object in a simple sim world. -- Ben How noisy is the sim world, e.g. number of distractions, difficulty of separating target object from ground? What types of variation can the target objects show e.g. additional parts or deformation? Have you experimented with identifying objects by their interactions in the simworld, not just their appearance to simulated vision or touch? ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
