On 12/7/06, Richard Loosemore <[EMAIL PROTECTED]> wrote:
Ben Goertzel wrote:
> 1) optimizing the set of subgoals chosen in pursuit of a given set of
> supergoals. This is well-studied in computer science and operations
> research. Not easy computationally or emotionally, but conceptually
> straightforward to understand.
When the target of the subgoals is defined as a set of complex
constraints operating over a large portion of the system's knowledge,
and when the system's knowledge is (at least sometimes) encoded in
non-explicit ways (i.e. cannot be exactly stated in predicate form), the
"optimization" of the subgoals becomes a type of problem that has not
been studied by computer science and operations research. (We are
talking about serious amounts of complex systems behavior here).
You might be able to state the problem in a way such that gradient
search or multiple linear regression would choose how to allocate your
resources among these subgoals. I know you don't like linear
approaches, Richard, but honestly, I doubt humans do better at
optimizing than linear approaches.
The concept of optimizing a supergoal seems to me to break down.
I agree with this - I don't know what you mean by optimizing a supergoal.
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