On 10/5/07, Richard Loosemore <[EMAIL PROTECTED]> wrote: > Mike Dougherty wrote: > > On 10/4/07, Richard Loosemore <[EMAIL PROTECTED]> wrote: > >> All understood. Remember, though, that the original reason for talking > >> about GoL was the question: Can there ever be a scientific theory that > >> predicts all the "interesting creatures" given only the rules? > >> > >> The question of getting something to recognize the existence of the > >> patterns is a good testbed, for sure. > > > > Given finite rules about a finite world with an en effectively > > unlimited resource, it seems that every "interesting creature" exists > > as the subset of all permutations minus the noise that isn't > > interesting. The problem is in a provable definition of interesting > > (which was earlier defined for example as 'cyclic') Also, who is > > willing to invest unlimited resource to exhaustively search a "toy" > > domain? Even if there were parallels that might lead to formalisms > > applicable in a larger context, we would probably divert those > > resources to other tasks. I'm not sure this is a bad idea. Perhaps > > our human attention span is a defense measure against wasting life's > > resources on searches that promise fitness without delivering useful > > results. > > I hear you, but let me quickly summarize the reason why I introduced GoL > as an example. > > I wanted to use GoL as a nice-and-simple example of a system whose > overall behavior (in this case, the existence of certain patterns that > are "stable" or "interesting") seems impossible to predict from a > knowledge of the rules.
You do predict that behavior by simulating the model. What you supposedly can't do is to find initial conditions that will lead to required global behavior. But you actually can - for example by enumerating possible initial conditions in a brute force way and looking at what happens when you simulate it. It's just very inefficient, and as a result you can't enumerate many initial conditions which will lead to interesting global behavior. And probably there are tricks to get better results, by restricting search space. You propose a framework which will help in efficient enumeration of low-level rules and estimation of high-level behavior, and restrain possibilities to as close as possible to existing working system - human mind. All along these same lines. Computational mathematics deals with this kind of thing all the time. -- Vladimir Nesov mailto:[EMAIL PROTECTED] ----- 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=50383288-697f70
