Richard,

Any problem can be stated as search for results that satisfy given
constraints. What you state here doesn't seem to contradict what I
wrote before. In following paragraph you describe it:

On 10/6/07, Richard Loosemore <[EMAIL PROTECTED]> wrote:
> In my use of GoL in the paper I did emphasize the prediction part at
> first, but I then went on (immediately) to talk about the problem of
> finding hypotheses to test.  Crucially, I ask if it is reasonable to
> suppose that Conway could have written down the patterns he *wanted* to
> see emerge, then found the rules that would generate his desired patterns.

So, you ask if it's possible to find local rule given global behavior.
It's obviously possible to get global behavior once you have local
rules. Which essentially what I wrote before, and what Josh
exemplified by his brute force initial conditions enumerator. I try
not to be 'dismissive', which suggests kind of oversight, but I also
try not to ignore inconsistencies.

On 10/5/07, Vladimir Nesov <[EMAIL PROTECTED]> wrote:
> 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]

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