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 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 makes
> this area of research (uncertain logic) "interesting" ...
>
> ben g
>
> On Sun, Oct 12, 2008 at 2:07 PM, Pei Wang <[EMAIL PROTECTED]> wrote:
>>
>> Abram: The parameter 'k' does not really depend on the future, because
>> it makes no assumption about what will happen in that period of time.
>> It is just a "ruler" or "weight" (used with scale) to measure the
>> amount of evidence, as a "reference amount".
>>
>> For other people: The definition of confidence c = w/(w+k) states that
>> confidence is the proportion of current evidence among future
>> evidence, after the coming of evidence of amount k.
>>
>> Pei
>>
>> On Sun, Oct 12, 2008 at 1:48 PM, Abram Demski <[EMAIL PROTECTED]>
>> wrote:
>> > 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 experience; they are calculated with prediction in
>> > mind.
>> >
>> > --Abram
>> >
>> > On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]>
>> > wrote:
>> >> A brief and non-technical description of the two types of semantics
>> >> mentioned in the previous discussions:
>> >>
>> >> (1) Model-Theoretic Semantics (MTS)
>> >>
>> >> (1.1) There is a world existing independently outside the intelligent
>> >> system (human or machine).
>> >>
>> >> (1.2) In principle, there is an objective description of the world, in
>> >> terms of objects, their properties, and relations among them.
>> >>
>> >> (1.3) Within the intelligent system, its knowledge is an approximation
>> >> of the objective description of the world.
>> >>
>> >> (1.4) The meaning of a symbol within the system is the object it
>> >> refers to in the world.
>> >>
>> >> (1.5) The truth-value of a statement within the system measures how
>> >> close it approximates the fact in the world.
>> >>
>> >> (2) Experience-Grounded Semantics (EGS)
>> >>
>> >> (2.1) There is a world existing independently outside the intelligent
>> >> system (human or machine). [same as (1.1), but the agreement stops
>> >> here]
>> >>
>> >> (2.2) Even in principle, there is no objective description of the
>> >> world. What the system has is its experience, the history of its
>> >> interaction of the world.
>> >>
>> >> (2.3) Within the intelligent system, its knowledge is a summary of its
>> >> experience.
>> >>
>> >> (2.4) The meaning of a symbol within the system is determined by its
>> >> role in the experience.
>> >>
>> >> (2.5) The truth-value of a statement within the system measures how
>> >> close it summarizes the relevant part of the experience.
>> >>
>> >> To further simplify the description, in the context of learning and
>> >> reasoning: MTS takes "objective truth" of statements and "real
>> >> meaning" of terms as aim of approximation, while EGS refuses them, but
>> >> takes experience (input data) as the only thing to depend on.
>> >>
>> >> As usual, each theory has its strength and limitation. The issue is
>> >> which one is more proper for AGI. MTS has been dominating in math,
>> >> logic, and computer science, and therefore is accepted by the majority
>> >> people. Even so, it has been attacked by other people (not only the
>> >> EGS believers) for many reasons.
>> >>
>> >> A while ago I made a figure to illustrate this difference, which is at
>> >> http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A
>> >> manifesto of EGS is at
>> >> http://nars.wang.googlepages.com/wang.semantics.pdf
>> >>
>> >> Since the debate on the nature of "truth" and "meaning" has existed
>> >> for thousands of years, I don't think we can settle down it here by
>> >> some email exchanges. I just want to let the interested people know
>> >> the theoretical background of the related discussions.
>> >>
>> >> Pei
>> >>
>> >>
>> >> On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote:
>> >>>
>> >>>
>> >>>
>> >>> Hi,
>> >>>
>> >>>>
>> >>>> > What this highlights for me is the idea that NARS truth values
>> >>>> > attempt
>> >>>> > to reflect the evidence so far, while probabilities attempt to
>> >>>> > reflect
>> >>>> > the world
>> >>>
>> >>> I agree that probabilities attempt to reflect the world
>> >>>
>> >>>>
>> >>>> .
>> >>>>
>> >>>> Well said. This is exactly the difference between an
>> >>>> experience-grounded semantics and a model-theoretic semantics.
>> >>>
>> >>> I don't agree with this distinction ... unless you are construing
>> >>> "model
>> >>> theoretic semantics" in a very restrictive way, which then does not
>> >>> apply to
>> >>> PLN.
>> >>>
>> >>> If by model-theoretic semantics you mean something like what Wikipedia
>> >>> says
>> >>> at http://en.wikipedia.org/wiki/Formal_semantics,
>> >>>
>> >>> ***
>> >>> Model-theoretic semantics is the archetype of Alfred Tarski's semantic
>> >>> theory of truth, based on his T-schema, and is one of the founding
>> >>> concepts
>> >>> of model theory. This is the most widespread approach, and is based on
>> >>> the
>> >>> idea that the meaning of the various parts of the propositions are
>> >>> given by
>> >>> the possible ways we can give a recursively specified group of
>> >>> interpretation functions from them to some predefined mathematical
>> >>> domains:
>> >>> an interpretation of first-order predicate logic is given by a mapping
>> >>> from
>> >>> terms to a universe of individuals, and a mapping from propositions to
>> >>> the
>> >>> truth values "true" and "false".
>> >>> ***
>> >>>
>> >>> then yes, PLN's semantics is based on a mapping from terms to a
>> >>> universe of
>> >>> individuals, and a mapping from propositions to truth values.  On the
>> >>> other
>> >>> hand, these "individuals" may be for instance **elementary sensations
>> >>> or
>> >>> actions**, rather than higher-level individuals like, say, a specific
>> >>> cat,
>> >>> or the concept "cat".  So there is nothing non-experience-based about
>> >>> mapping terms into a "individuals" that are the system's direct
>> >>> experience
>> >>> ... and then building up more abstract terms by grouping these
>> >>> directly-experience-based terms.
>> >>>
>> >>> IMO, the dichotomy between experience-based and model-based semantics
>> >>> is a
>> >>> misleading one.  Model-based semantics has often been used in a
>> >>> non-experience-based way, but that is not because it fundamentally
>> >>> **has**
>> >>> to be used in that way.
>> >>>
>> >>> To say that PLN tries to model the world, is then just to say that it
>> >>> tries
>> >>> to make probabilistic predictions about sensations and actions that
>> >>> have not
>> >>> yet been experienced ... which is certainly the case.
>> >>>
>> >>>>
>> >>>> Once
>> >>>> again, the difference in truth-value functions is reduced to the
>> >>>> difference in semantics, what is, what the "truth-value" attempts to
>> >>>> measure.
>> >>>
>> >>> Agreed...
>> >>>
>> >>> Ben G
>> >>>
>> >>> ________________________________
>> >>> agi | Archives | Modify Your Subscription
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>> >>
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>
>
> --
> Ben Goertzel, PhD
> CEO, Novamente LLC and Biomind LLC
> Director of Research, SIAI
> [EMAIL PROTECTED]
>
> "Nothing will ever be attempted if all possible objections must be first
> overcome "  - Dr Samuel Johnson
>
>
> ________________________________
> agi | Archives | Modify Your Subscription


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