Jim:  First, a meme cannot be modelled in the same way a superficial data 
string can be.

http://en.wikipedia.org/wiki/Memetic_algorithm
In the lingua of MA a meme is a strategy; individuals within populations are 
recombined.
In PAM-P2 a solution is an individual, and solutions do undergo recombination 
and mutation during regulation and compensation.
~PM.
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The wikipedia definition of memetics was interesting.  Assuming that I can make 
a pretty good guess about how your idea of memetic recombination might work, I 
would say that your imagined usage of the method has some serious problems.  
First, a meme cannot be modelled in the same way a superficial data string can 
be so the comparison of memetic algorithms to recombination in genetic 
algorithms seems fanciful.  Secondly the idea that the attributes of a concept 
might be clearly differentiated in an automated system that is able to learn 
and then used to clearly integrate different ideas seems unlikely.  I do not 
think the concept is impossible, I think that it is complicated.  It is a 
problem of complexity.  You mentioned that you thought you can avoid complexity 
by using many small search problems.  Although I cannot point to this or that 
study which can drive this point home, I do feel that there is ample evidence 
that domain restricted learning has not worked in AI just because we need to 
use concepts outside of the domain in order to understand those concepts which 
are strongly within the domain.  (By the way, here is where an imagined 
efficiency of using weighted evaluations can really turn to nonsense. You can't 
eliminate the need to look outside the domain to determine meaning or relevance 
just by putting a numerical value on how much a meme belongs to a particular 
domain.) 
  Jim Bromer 

                                          


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AGI
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