On Tue, Sep 30, 2008 at 12:45 PM, Mike Tintner <[EMAIL PROTECTED]>wrote:
> Ben: the reason AGI is so hard has to do with Santa Fe Institute style > complexity ... > > Intelligence is not fundamentally grounded in any particular mechanism but > rather in emergent structures > and dynamics that arise in certain complex systems coupled with their > environments > > Characterizing what these emergent structures/dynamics are is hard, > > Ben, > > Maybe you could indicate how complexity might help solve any aspect of > *general* intelligence - how it will help in any form of crossing domains, > such as analogy, metaphor, creativity, any form of resourcefulness etc.- > giving some example. > > > Personally, I don't think it has any connection - and it doesn't sound > from your last sentence, as if you actually see a connection :). > You certainly draw some odd conclusions from the wording of peoples' sentences. I not only see a connection, I wrote a book on this subject, published by Plenum Press in 1997: "From Complexity to Creativity." Characterizing these things at the conceptual and even mathematical level is not as hard at realizing them at the software level... my 1997 book was concerned with the former. I don't have time today to cut and paste extensively from there to satisfy your curiosity, but you're free to read the thing ;-) ... I still agree with most of it ... To give a brief answer to one of your questions: analogy is mathematically a matter of finding mappings that match certain constraints. The traditional AI approach to this would be to search the constrained space of mappings using some search heuristic. A complex systems approach is to embed the constraints into a dynamical system and let the dynamical system evolve into a configuration that embodies a mapping matching the constraints. Based on this, it is provable that complex systems methods can solve **any** analogy problem, given appropriate data, and using for example asymmetric Hopfield nets (as described in Amit's book on Attractor Neural Networks back in the 80's). Whether they are the most resource-efficient way to solve such problems is another issue. OpenCog and the NCE seek to hybridize complex-systems methods with probabilistic-logic methods, thus alienating almost everybody ;=> -- Ben G ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
