I have still been doing some work... FYI, the formula in my most
recent proposal still isn't quite right, that's pretty obvious now.
The right formula can be found by solving a differential eqn, but I am
no good at this, and of course there may not be a solution to it... if
I could just prove there was *some* solution w/o needing to find it!
Anyway, maybe I will post more soon??

--Abram

On Wed, Oct 1, 2008 at 7:30 PM, Brad Paulsen <[EMAIL PROTECTED]> wrote:
>
> Ben wrote: "I remain convinced that probability theory is a proper
> foundation for uncertain inference in an AGI context, whereas Pei remains
> convinced of the opposite....So, this is really the essential issue, rather
> than the particularities of the algebra..."
>
> But, please, don't stop discussing that algebra.  This is the most fun I've
> had on an e-mail list in years!
>
> Cheers,
> Brad
>
> Ben Goertzel wrote:
>>
>>
>> On Tue, Sep 23, 2008 at 9:28 PM, Pei Wang <[EMAIL PROTECTED]
>> <mailto:[EMAIL PROTECTED]>> wrote:
>>
>>     On Tue, Sep 23, 2008 at 7:26 PM, Abram Demski <[EMAIL PROTECTED]
>>     <mailto:[EMAIL PROTECTED]>> wrote:
>>     > Wow! I did not mean to stir up such an argument between you two!!
>>
>>     Abram: This argument has been going on for about 10 years, with some
>>     "on" periods and "off" periods, so don't feel responsible for it ---
>>     you just raised the right topic in the right time to turn it "on"
>>     again. ;-)
>>
>>
>>
>> Correct ... Pei and I worked together on the same AI project for a few
>> years
>> (1998-2001) and had related arguments in person many times during that
>> period,
>> and have continued the argument off and on over email...
>>
>> It has been an interesting and worthwhile discussion, from my view any way,
>> but neither of us has really convinced the other...
>>
>> I remain convinced that probability theory is a proper foundation for
>> uncertain
>> inference in an AGI context, whereas Pei remains convinced of the
>> opposite ...
>>
>> So, this is really the essential issue, rather than the particularities
>> of the
>> algebra...
>>
>> The reason this is a subtle point is roughly as follows (in my view, Pei's
>> surely differs).
>>
>> I think it's mathematically and conceptually clear that for a system
>> with unbounded
>> resources probability theory is the right way to reason.   However if
>> you look
>> at Cox's axioms
>>
>> http://en.wikipedia.org/wiki/Cox%27s_theorem
>>
>> you'll see that the third one (consistency) cannot reasonably be expected of
>> a system with severely bounded computational resources...
>>
>> So the question, conceptually, is: If a cognitive system can only
>> approximately
>> obey Cox's third axiom, then is it really sensible for the system to
>> explicitly
>> approximate probability theory ... or not?  Because there is no way for
>> the system
>> to *exactly* follow probability theory....
>>
>> There is not really any good theory of what reasoning math a system should
>> (implicitly or explicitly) emulate given limited resources... Pei has
>> his hypothesis,
>> I have mine ... I'm pretty confident I'm right, but I can't prove it ...
>> nor can he
>> prove his view...
>>
>> Lacking a comprehensive math theory of these things, the proof is gonna be
>> in the pudding ...
>>
>> And, it is quite possible IMO that both approaches can work, though they
>> will
>> not fit into the same AGI systems.  That is, an AGI system in which NARS
>> would
>> be an effective component, would NOT necessarily
>> look the same as an AGI system in which PLN would be an effective
>> component...
>>
>> Along these latter lines:
>> One thing I do like about using a reasoning system with a probabilistic
>> foundation
>> is that it lets me very easily connect my reasoning engine with other
>> cognitive
>> subsystems also based on probability theory ... say, a Hawkins style
>> hierarchical
>> perception network (which is based on Bayes nets) ... MOSES for
>> probabilistic
>> evolutionary program learning etc.   Probability theory is IMO a great
>> "lingua
>> franca" for connecting different AI components into an integrative whole...
>>
>> -- Ben G
>>
>>
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