2008/9/8 Benjamin Johnston [EMAIL PROTECTED]:
Does this issue actually crop up in GA-based AGI work? If so, how did you
get around it? If not, would you have any comments about what makes AGI
special so that this doesn't happen?
Does it also happen in humans? I'd say yes, therefore it might
Hi,
I am curious about the result you mention. You say that the genetic
algorithm stopped search very quickly. Why? It sounds like they want
to search to go longer, but can't they just tell it to go longer if
they want it to? And to reduce convergence, can't they just increase
the level of
You can implement a new workaround to bootstrap your organisms past
each local maximum, like catalyzing the transition from water to land
over and over. I find this leads to cheats that narrow the search in
unpredictable ways, though. This problem comes up again and again.
Maybe some kind of
Hi,
I have a general question for those (such as Novamente) working on AGI
systems that use genetic algorithms as part of their search strategy.
A GA researcher recently explained to me some of his experiments in
embedding prior knowledge into systems. For example, when attempting to
I'd just keep a long list of high scorers for regression and
occasionally reset the high score to zero. You can add random
specimens to the population as well...
On 9/7/08, Benjamin Johnston [EMAIL PROTECTED] wrote:
Hi,
I have a general question for those (such as Novamente) working on AGI
