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.
I meant I am going to try to make 4 different 4 pixel blurs for each pixel so that it will be grouped with different compositions of neighboring pixels. (For some reason this would take 9 different overlapping squares if it was applied to an initial square, but I am not sure if that is necessary.) This way I might be able to reduce the pixilation while at the same time I might be able to find the edges that I am looking for. On Fri, Feb 8, 2013 at 10:22 AM, Jim Bromer <[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 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
