On Fri, Feb 8, 2013 at 4:18 PM, Eugene Surowitz <[email protected]> wrote: But this presupposes the existence of known complete algorithm sets; I don't recall the establishment of the existence of such sets. ----------------------
We are not aware of definitions of families of algorithms (beyond extremely simple examples) because they have not been defined in a systematic way. Almost all functions or algorithms can be modified and many modifications can be made incrementally. This is done all the time. However, modifications to an algorithm may change the algorithm radically even if the algorithms are made incrementally. This means that there is no clear distinction between families of algorithms. A definition of a family of algorithms is therefore arbitrary. However, the same argument can be made about families of mathematical systems. It would be easy for me to use the system I came up with for the typological character generator to define a wide ranging algorithm generator, but I cannot say before hand that it would be elegant. I presume that my first attempts will be awkward and ungainly - and probably a little uncontrollable. However, it is clear to me now that this is something for the future. Jim Bromer On Fri, Feb 8, 2013 at 4:18 PM, Eugene Surowitz <[email protected]> wrote: > Ben: > In mathematics, there is the concept of "complete sets of functions" > which has many actual realizations, eg, Bessel functions, etc. > > This raises the idea that there could possibly be complete sets > of algorithms. If different sets can be given the task to approximate > behavior, in parallel, and in analogy to CSFs, some approximating > algorithm would probably win the race and terminate the search > for the needed algorithm. But this presupposes the existence of > known complete algorithm sets; I don't recall the establishment > of the existence of such sets. > > Cheers, Gene > > > On 2/8/2013 10:38 AM, Ben Goertzel wrote: > >> >> "Automated program learning" is a branch of AI that seems close to what >> you have in >> mind... >> >> This is what the MOSES component of OpenCog attempts to do, though it's >> currently >> only really effective at learning simple sorts of programs... >> >> -- Ben G >> >> On Fri, Feb 8, 2013 at 10:22 AM, Jim Bromer <[email protected] >> <mailto:[email protected]>> wrote: >> >> I was wondering if an algorithm generator might be useful for an AGI >> project.A >> super algorithm generator probably would not be so good because of >> the number of >> parameters that would be required to denote a collection of particular >> (generated) algorithms which had been found to be useful.If multiple >> algorithm >> >> generators were used, most of which were able to generate algorithms >> that could >> interact with the other kinds of algorithms that were generated, then >> each >> generator would need fewer parameters and you would only need to >> define the >> parameters for those combinations which were needed.Another way is to >> use a few >> >> super generators where each parameter that was used would have to be >> explicitly >> designated and those that weren't designated could just be ignored. >> >> The reason an algorithm generator might be useful because it might >> make sense to >> generate only those algorithms which were needed without creating >> millions of >> other algorithms which were not very useful.We all keep seeing how >> narrow AI can >> >> be achieved and there are reasons to believe that using many >> individual >> algorithms to analyze and decipher data and derive other related data >> may be the >> way to go. >> >> Let me explain why I thought that a super algorithm generator could >> be used in a >> concise manner.I originally was trying to think of an algorithm that >> did not take >> >> any input but which could create an overwhelming number of different >> variations >> of a typographical character.I wondered how I might program the >> generator >> >> effectively to convince a skeptic that it was capable of producing an >> immensity >> of different variations.I was worried that if it simply iterated its >> way through >> >> the parameters that it would get stuck on one variation and it might >> look like it >> was just producing the same kind of variations of one style over and >> over >> again.(This is what happens when a great video game starts to bore >> you).So I came >> >> up with the use of random number generators to generate the >> parameters.Another >> method is to use a number generator that can produce non-sequential >> string of >> numbers which did not begin outputting a repeating substring (like a >> decimal >> expansion of a rational number).I don't know how to do this >> efficiently but I >> >> believe that there may be some way. >> >> So the super algorithm generator probably would not work well in an >> AGI program >> because it would not be efficient to implement it under the demands >> of a >> practical system.However, the component algorithm generators might >> make more >> sense and it is an interesting idea to think about.I can describe a >> toy model, >> >> but it will seem so familiar that some programmers might think that >> they had >> already thought of using algorithm generators in their programming >> just because >> they have so much personal experience generating variations of >> algorithms. >> >> Suppose you are analyzing an image and your algorithm is not working >> because of >> the pixilation.What do you do?I tried a blurring algorithm to blur >> the image >> slightly.So by taking 4 pixels in a square (or 9 or 16) and averaging >> them out I >> can reduce the pixilation a little bit.This could be done by changing >> the >> parameters in a rgb algorithm generator.If an AGi program was able to >> develop >> >> some kind of reasoning about a problem and its attention was directed >> toward >> pixilation it might be able to notice that blur algorithms can reduce >> pixilation. >> However, the blur algorithm did not work for my problem. I was trying >> to extend >> the abilities of a line drawing algorithm and the simple blur >> algorithm blurred >> the very kinds of lines that I was looking for.So, in order to try to >> make sure >> >> that I do not blur the distinctiveness between shapes I am going to >> try to make 9 >> different 4 pixel blurs so that each pixel will be grouped with >> different >> compositions of neighboring pixels.This way I might be able to detect >> a strong >> >> contrast line or a demarcation between different colored shapes. >> >> This toy problem shows how the algorithm generator might work if some >> essential >> reasoning between a desired goal and actual results could be made on >> the basis of >> a collection of observations of how individual rgb algorithms act on >> various >> images.One of the problems in AI is that we do not know how to take >> the >> >> 'observation' of directly inputted data to discover the meaning of >> that data and >> how it relates to other data objects. However, the substitution of a >> goal is >> often easier.Once attention is drawn to some effect, the goal of >> recreating that >> >> effect in other situations may be something that a simple AGi program >> can >> realize.So if a goal is clearly definable (for an AGi program) and >> there are >> >> examples of generated algorithms that were capable of reaching the >> desired >> effect for some cases and there was some basis for believing that an >> modification >> of some group of parameters might enhance the desired characteristics >> of those >> algorithms for the more difficult cases, then this idea might be >> useful.Another >> reason that this idea of algorithm generators might be useful is >> because they >> might be used to standardize processes of discovery in an AGI >> program.So I am >> >> going to continue thinking about this. >> >> Jim Bromer >> >> *AGI* | Archives >> <https://www.listbox.com/**member/archive/303/=now<https://www.listbox.com/member/archive/303/=now> >> > >> >> <https://www.listbox.com/**member/archive/rss/303/212726-**deec6279<https://www.listbox.com/member/archive/rss/303/212726-deec6279>> >> | Modify >> <https://www.listbox.com/**member/?&;<https://www.listbox.com/member/?&;>> >> Your Subscription [Powered by Listbox] >> <http://www.listbox.com> >> >> >> >> >> >> -- >> Ben Goertzel, PhD >> http://goertzel.org >> >> "My humanity is a constant self-overcoming" -- Friedrich Nietzsche >> *AGI* | Archives >> <https://www.listbox.com/**member/archive/303/=now<https://www.listbox.com/member/archive/303/=now> >> > >> <https://www.listbox.com/**member/archive/rss/303/**12987897-64924e57<https://www.listbox.com/member/archive/rss/303/12987897-64924e57>> >> | Modify >> <https://www.listbox.com/**member/?&; <https://www.listbox.com/member/?&;>> >> Your >> Subscription [Powered by Listbox] <http://www.listbox.com> >> >> > > > ------------------------------**------------- > AGI > Archives: > https://www.listbox.com/**member/archive/303/=now<https://www.listbox.com/member/archive/303/=now> > RSS Feed: https://www.listbox.com/**member/archive/rss/303/** > 10561250-470149cf<https://www.listbox.com/member/archive/rss/303/10561250-470149cf> > Modify Your Subscription: https://www.listbox.com/** > member/?&id_**secret=10561250-b8cb8eb9<https://www.listbox.com/member/?&;> > Powered by Listbox: http://www.listbox.com > ------------------------------------------- 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
