Monday, February 04, 2008 8:22 PM, Ravi Sharma wrote: (01)
I am afraid comments will take us in multiple directions (but central point
is single ontology is far-far away) ...
We are very-very far but in physics - unification is known frontier at
integrated theories but far from single formalism of universe?. (02)
Dear Ravi, (03)
Let me assure you that the single ontology is not so far as we might think.
The problem is, most good minds are too specialized, special, specific, and
particular. And allow me to remind that the crowning achievement of science
is to give an integrated account of the world, presented as one mathematical
(or conceptual) formalism of the universe. (04)
Some brief comments below.
Many thanks,
Azamat (05)
----- Original Message -----
From: "Sharma, Ravi" <Ravi.Sharma@xxxxxxxxxxx>
To: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
Sent: Monday, February 04, 2008 8:22 PM
Subject: Re: [ontolog-forum] Axiomatic ontology (06)
> Azamat
>
> I am afraid comments will take us in multiple directions (but central
> point is single ontology is far-far away):
>
> 1. Inherently many natural phenomena are Non linear - a bit difficult to
> handle but need not necessarily be non-continuous. (07)
the real state of things is usually opposite to our expectations. All
natural phenomena are nonlinear, and determined by nonlinear causality. (08)
> 2. Quantum to continuous is only conceptual. Coexistence is allowed in
> physics by Duality. Wanting to describe fine grained phenomena in coarse
> grains tends to be better (today, in tools) with continuous
> representations.
There are two types of quantum (quantity), which are discrete, like number
and speech, and continuous, like time and space. (09)
> 3. Are Thoughts Quanta? These are often random and discrete? Brain PET
> scans may say something but from past historic studies, these are often
> disconnected if viewed in time sequence - at least pseudo-random! (010)
Thoughts are uninterrupted acts, kinds of mental processes, ordered,
continuous, coherent and logical. Otherwise it is a muss. (011)
> 4. Chaos - is it continuous or discrete, random - partly deterministic
> and partly stochastic? (012)
Chaos is a deterministic phenomenon, guided by a complex causality, a
nonlinear interaction of states, changes, or processes. (013)
> 5. Assuming one ontology to describe whole universe is expecting that
> everyone is at the same wisdom level as the cause that caused "all this
> universe at least", if not beyond it, and if there is one single cause?
> We are very-very far but in physics - unification is known frontier at
> integrated theories but far from single formalism of universe? (014)
The ultimate goal of physics is a theory of everything, but physical; while
the ultimate objective of real ontology is a theory of everything in the
full sense, physical, chemical, biological, psychological, social, etc.
>
> Thanks.
>
> Ravi
>
> (Dr. Ravi Sharma) Senior Enterprise Architect
>
> Vangent, Inc. Technology Excellence Center (TEC)
>
> 8618 Westwood Center Drive, Suite 310, Vienna VA 22182
> (o) 703-827-0638, (c) 313-204-1740 www.vangent.com
>
>
> -----Original Message-----
> From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
> [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Azamat
> Sent: Sunday, February 03, 2008 3:34 PM
> To: [ontolog-forum]
> Subject: Re: [ontolog-forum] Axiomatic ontology
>
> Sunday, February 03, 2008 9:15 AM, Francis McCabe wrote:
>
> ''I think that what is going on may be a little deeper.... Now, there is
>
> some evidence that the universe is not truly continuous:
> it may be granular both with respect to space and with respect to
> time.''
>
> The universe is the largest continuous entity, continuing both in time
> and
> space. The chaos theory doesn't mystify the nature of the world more
> than it
> is. But it evidences to its puzzling complexity, it attests that the
> universe is a cosmic-scale nonlinear dynamic complex system governed by
> reciprocal interactions of its numerous parts.
>
>
>
> All nonlinear effects in nature and society studied by nonlinear
> sciences
> and represented by nonlinear equations can be accounted by the same
> causal
> mechanisms: nonlinear causality (as causal loops) producing nonlinear
> self-acting phenomena (expressed as soliton solutions), as in general
> relativity, nonlinear QM, nonlinear optics, the planet's weather system,
>
> global economy and finance and international politics. A timely
> appreciation
> of nonlinear effects in the global stock exchange allowed Soros (and his
>
> Quantum Fund) reputedly to make billions, knowing the nonlinear behavior
> of
> economic fundamentals and risk-factors such as interest rates,
> commodities,
> currencies, stock indices.
>
>
>
> The implication of chaos is the complexity of causality as the nonlinear
>
> relationships between changes, processes or events, where a small input
> change (infinitesimal disturbances in the initial conditions) in one
> part of
> a complex system may end up in a large effect in toto.
>
>
>
> So, the real meaning of ''chaos'' is not ''disorder'' but rather a
> higher-order dynamic organization; for a chaotic system is a
> deterministic
> and principally predictable phenomenon, whose behavior is determined by
> nonlinear causal laws.
>
> The moral of the whole story is to build a consistent ontology of
> entities
> and relationships, including such a unique natural phenomenon as a
> nonlinear
> causality http://en.wikipedia.org/wiki/Causality.
>
>
>
> Azamat Abdoullaev
>
>
>
>
> ----- Original Message -----
> From: "Francis McCabe" <frankmccabe@xxxxxxx>
> To: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
> Sent: Sunday, February 03, 2008 9:15 AM
> Subject: Re: [ontolog-forum] Axiomatic ontology
>
>
>>I think that what is going on may be a little deeper.
>>
>> Stipulating for a moment the continuous function argument. In any
>> digital system, in any countable system actually, you can approximate
>> a real number's value to any desired level of precision.
>>
>> Now, there is some evidence that the universe is not truly continuous:
>> it may be granular both with respect to space and with respect to
> time.
>>
>> If your approximation of a continuous function is more accurate than
>> that granularity, then it can make no difference in the observed
>> results. I.e., digital simulations of fractal functions and chaotic
>> predictions can be as accurate as the universe will allow anyway.
>>
>> However, the weather man does not need to go to this level of accuracy
>> to get results that are best explained in terms of chaos theory. The
>> results of a prediction are unstable at any level of accuracy: the
>> higher the accuracy the longer the stable prediction; but the pattern
>> is the same.
>>
>>
>> On Feb 2, 2008, at 10:34 PM, Rob Freeman wrote:
>>
>>> On Feb 3, 2008 12:11 PM, Randall R Schulz <rschulz@xxxxxxxxx> wrote:
>>>> On Saturday 02 February 2008 19:47, Rob Freeman wrote:
>>>>>
>>>>> Why can't we model chaotic behaviour on a digital computer Randall?
>>>>
>>>> Because digital computers cannot represent or process real numbers.
>>>
>>> That's a good point.
>>>
>>> Here's Wikipedia to put it in context:
>>>
>>> "An early pioneer of the theory was Edward Lorenz whose interest in
>>> chaos came about accidentally through his work on weather prediction
>>> in 1961. Lorenz was using a simple digital computer, a Royal McBee
>>> LGP-30, to run his weather simulation. He wanted to see a sequence of
>>> data again and to save time he started the simulation in the middle
> of
>>> its course. He was able to do this by entering a printout of the data
>>> corresponding to conditions in the middle of his simulation which he
>>> had calculated last time.
>>>
>>> To his surprise the weather that the machine began to predict was
>>> completely different from the weather calculated before. Lorenz
>>> tracked this down to the computer printout. The computer worked with
>>> 6-digit precision, but the printout rounded variables off to a
> 3-digit
>>> number, so a value like 0.506127 was printed as 0.506. This
> difference
>>> is tiny and the consensus at the time would have been that it should
>>> have had practically no effect. However Lorenz had discovered that
>>> small changes in initial conditions produced large changes in the
>>> long-term outcome. Lorenz's discovery, which gave its name to Lorenz
>>> attractors, proved that meteorology could not reasonably predict
>>> weather beyond a weekly period (at most)."
>>> http://en.wikipedia.org/wiki/Chaos_theory
>>>
>>> So this presents a problem.
>>>
>>> To draw the analogy, though, Lorenz didn't react to his discovery by
>>> abandoning computer modeling of the weather, or by assuming the
>>> weather was not really chaotic after all. He just accepted that tiny
>>> inaccuracies meant that any digital copy of the weather would diverge
>>> from the original over time.
>>>
>>> I'm guessing chaos is still assumed in all modern models of the
>>> weather, and further I'm assuming all those models are still digital.
>>>
>>> Digital models of the weather may be imperfect, but presumably to
>>> ignore chaos when you try to model the weather is not to model the
>>> weather at all.
>>>
>>> Note: there's an interesting corollary to this idea of sensitivity to
>>> arbitrarily small differences in initial conditions. It would mean
>>> that, assuming a chaotic model, any "copy" we might one day be able
> to
>>> make of an individual's thoughts would immediately start to diverge
>>> from the original. So while one day it may be possible to copy
>>> someone's thoughts, according to this model it would never be
> possible
>>> to predict them (beyond a week or so :-)
>>>
>>> -Rob
>>>
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>>
>>
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