2008/1/7, David Butler <[EMAIL PROTECTED]>: > > How would an AGI choose which things to learn first if given enough > data so that it would have to make a choice?
This is a simple question that demands a complex answer. It is like asking "How can a commercial airliner fly across the Atlantic?". Well, in that case you would have to study aerodynamics, mechanics, physics, thermodynamics, computer science, electronics, metallurgy and chemistry for several years, and in the end you would discover that one single person cannot understand such a complex machine in its entire detail. True enough, one person could understand all basic principles for such a system, but explaining them would hardly suffice as evidence that it would actually work in practice. If you lived in the medieval times, and someone asked you "how is it possible to cross the Atlantic in a flying machine carrying several hundred passengers?", what would you answer? Even if you had the expertise knowledge it would be very hard to explain thoroughly, just because the machine is so complex and you would have to explain every technology from the beginning. Where would you start? Maybe some person with less insight would interrupt you after a few sentences and say "well, clearly you cannot present evidence that it will ever work" and make fun of the idea, but how does insufficient time/space to explain a complex system prove that something is not possible? The same goes for AGI, for example when someone asks "how can we create a program that is creative and can choose what to learn?". In response to this it is possible to present a lot of different principles, such as adaptability, genetic programming, quelling of combinatorial explosions etc. But will the principles work in practice when put together? Well, at this stage we simply cannot tell. *So every person just has to make a choice in whether to believe it is possible, or whether to believe it is not possible. *But just because no AGI researcher can answer that question in a few words. "how can we create a programs that is creative and can choose what to learn", it doesn't mean it is not possible when all these principles come together. We just have to wait and see. To those who do not believe: Please just go away from this mailing list and do not interfere with the work here. Don't demand proof that it would work, because when we have such proof, i.e. a finished AGI system, we wont need to defend our hypothesises anyway. If two AGI's (again-same > hardware, learning programs and controlled environment) were given > the same data would they make different choices? Is a deterministic system deterministic? I do not understand what you are getting at. Why this question? I think Benjamin answered this question pretty thoroughly already. /Robert Wensman ----- 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=8660244&id_secret=82686766-4e2400
