2008/9/21 Pei Wang <[EMAIL PROTECTED]>:
> There are several issues involved in this example, though the basic is:
>
> (1) There is a decision to be made before a deadline (after 10 days),
> let's call it goal A, written as A?
> (2) At the current moment, the available information is not enough to
> support a confident conclusion, that is, the system has belief A<f,c>,
> though the confidence c is below the threshold (to trigger an
> immediate betting action).

Can you get it so that without the knowledge of the possibility of
future information it would still act? E.g. is the threshold
adjustable in some way.

> (3) It is known that future evidence B (the weather in russia 5 day
> before the deadline) will provide a better solution, that is, B==>A
> with a high <f,c>.

It is this step I am interested in.

Normally knowing X does not imply that you know X is useful for
solving all problems that X is useful for helping to solve.  If I tell
you that Gordon Brown the current Prime Minister of the UK is in
political difficulties, you don't know that this will be useful for
answering a prize quiz question such as, "Who resigned after losing a
party leadership election this week" (it hasn't happened yet, but
might do).  You might figure out that the fact I gave is useful for
this question and then guess the answer is Gordon Brown, without
having better information.

So there would need to be some form of search or linkage, so that you
construct the potential usefulness of facts as yet unknown, with their
usefulness as parts of the solution of problems.

Does NARS do this?

I should probably reformulate the scenario as the problem of which
question to phone a friend on "Who wants to be a millionaire". I shall
try and do so.

  Will Pearson


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agi
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