Jim, Everything hinges on what problems you are attempting to solve and how you frame those problems. I know specifically what problems I'm addressing. But it sounds to me that you have not defined the larger problems well enough for yourself to tackle them with any known methods. You have to be more specific. What do you mean by "in all significant cases"? Examples please. What do you mean by "solve the kinds of problems that you would need to solve"? Examples please. "It seems obvious to me that a memetic algorithm is not a breakthough method that would make an AGI program feasible". Is it the case that you'll know the breakthrough algorithm when you see it? It'll be obvious to everyone? What are the characteristics of such a breakthrough algorithm that will enable you to recognize it? And will it be a single algorithm or a combination of algorithmsthat will enable AGI? Please be specific. Everything hinges on what how you frame the "AGI problem" and the methods you employ to address it. I know which problems I'm trying to solve. ~PM.
Date: Thu, 6 Dec 2012 15:50:46 -0500 Subject: Re: [agi] Memetic algorithms From: [email protected] To: [email protected] Memetic algorithms sound like more of the same. Maybe I am not getting it but it doesn't sound like it is going to lead to anything that less formalized methods haven't been able to do. It seems obvious to me that a memetic algorithm is not a breakthrough method that would make an AGI program feasible. You say that a meme is a strategy? Before I read the thing on Memetic Algorithms I thought that that remark made perfect sense, but now that I have read it I am wondering what are you talking about? I mean really. A genetic algorithm is a neat thing, ok and I can understand that a variation on it is very interesting. But to believe that it will solve the kinds of problems that you would need it to solve is inexplicable. This is not a solution to np-complexity it is a generator of it. Isn't it obvious? Have I missed some great efficacy that lurks in the method that was hidden in my superficial reading of the description in Wikipedia? If I had I am pretty sure I would have sensed it. A concept or a meme cannot (reliably or always) be decomposed into a set of elemental parts. Because the parts of the concept are concepts themselves they can be studied, further explored, expanded and grouped with other related concepts. This is a property that I call relativistic. Of course you can use recombinations of concepts and memes and that method is necessary for imaginative projection and analysis and so on. But to believe that a method like memetic algorithms would lead to greater comprehension - in all significant cases - does not seem like a reasonable presumption to me. Jim Bromer On Thu, Dec 6, 2012 at 1:43 PM, Piaget Modeler <[email protected]> wrote: 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. ------------- 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 AGI | Archives | Modify Your Subscription AGI | Archives | Modify Your Subscription ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
