Thanks Pei,
I would add (for others, obviously you know this stuff) that there are many
different
theoretical justifications of probability theory, hence that the use of
probability
theory does not imply model-theoretic semantics nor any other particular
approach to semantics.
My own philosophy
Ben,
Of course, probability theory, in its mathematical form, is not
bounded to any semantics at all, though it implicitly exclude some
possibilities. A semantic theory is associated to it when probability
theory is applied to a practical situation.
There are several major schools in the
Pei,
In this context, how do you justify the use of 'k'? It seems like, by
introducing 'k', you add a reliance on the truth of the future after
k observations into the semantics. Since the induction/abduction
formula is dependent on 'k', the truth values that result no longer
only summarize
On the other hand, in PLN's indefinite probabilities there is a parameter k
which
plays a similar mathematical role, yet **is** explicitly interpreted as
being about
a number of hypothetical future observations ...
Clearly the interplay btw algebra and interpretation is one of the things
that
True. Similar parameters can be found in the work of Carnap and
Walley, with different interpretations.
Pei
On Sun, Oct 12, 2008 at 2:11 PM, Ben Goertzel [EMAIL PROTECTED] wrote:
On the other hand, in PLN's indefinite probabilities there is a parameter k
which
plays a similar mathematical
Pei,
You are right, it doesn't make any such assumptions while Bayesian
practice does. But, the parameter 'k' still fixes the length of time
into the future that we are interested in predicting, right? So it
seems to me that the truth value must be predictive, if its
calculation depends on what
On Sun, Oct 12, 2008 at 3:06 PM, Abram Demski [EMAIL PROTECTED] wrote:
Pei,
You are right, it doesn't make any such assumptions while Bayesian
practice does. But, the parameter 'k' still fixes the length of time
into the future that we are interested in predicting, right? So it
seems to me
