how does your system or these other systems that you are talking about, represent "goals" , "move", "obstacle".. "path.."? Literally, what form do those concepts take within any of these systems -and what meanings/sense/ referents are attached to them and how? Do they actually use the general concept "goal" as such - as distinct, obviously, from having their own specific goals?
Now you are asking about "how it works", though ;-) As noted in available review papers on NM, Novamente uses a multi-aspect knowledge representation, in which something like "obstacle" would be represented: -- declaratively, as nodes and links representing probabilistic relations -- as an overall "attractor pattern" of activity across the whole node/link network of memory -- visually, as a set of "internal movies" in NM's internal simulation I am actually writing a paper on knowledge representation, and will post it to this list within the next couple weeks. That should provide a good basis for discussing the question you've asked above. You see, if any computer system can represent those concepts as the human
brain actually does, then I would suggest that it's at least half solved the problem of AGI.
Well, NM is not a brain emulator and doesn't really have the goal of emulating the human brain's knowledge representation in any detail.... But I do think the human brain's KR is multi-aspect in the same general way that NM's is, as I've very roughly described above... -- Ben ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=fabd7936
