True. The more fundamental point is that symbols representing entities and concepts need to be grounded with (scalar) attributes of some sort.
How this is *implemented* is a practical matter. One important consideration for AGI is that data is easily retrievable by vector distance (similarity) and that new patterns can be leaned (unlearned) incrementally. Peter http://adaptiveai.com/ -----Original Message----- Behalf Of Ben Goertzel Well, the fact that clustering requires vectors for A2I2, is a property of your particular AI algorithms... Our Novamente clustering MindAgent is based on the Bioclust clustering algorithm, which does not act on vectors: ... Translating textual experience directly into weighted graphs is often more natural than translating it into vectors. A lot of NLP frameworks use graph representations.... ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
