Dear Thomas, Ravi, John, Hans et al,
TJ> Surely
there are no algorithms for deriving anyone's ontology.
I don't think you can say
that at this point. Let me try a simple statement:
Tell the subject to think of
an animal. Tell the subject to guess the animal in the familiar 20 questions
manner. Continue with the questions, ever more and more specific, until you
guess the actual animal. If it take more than 20 questions, that's
acceptable. Ask about properties, classes, situations, enablers, inhibitors, foods,
young, and any other question that can split the set of plausible answers in
half each time.
The point is, you can ask
someone leading questions until you have discovered the person's ontology to
some extent. The problem with such a cumbersome method is that you have to ask
a lot of questions to get the whole thing known. So designing a questionnaire
that can be used to separate philosophical viewpoints should be feasible, and
should result in a view of the subject's stated ontology, if not the subject's
actual ontology.
TJ> And
the best heuristic remains Quine's: we express our ontological commitments in
what we are willing to quantify over. "There exists an x such that
...." expresses a commitment to a kind (a universal whose instantiations
are particulars), as well as claiming that there in fact is at least one such
instantiation.
Yes, I have heard philosophers
on this list discuss "ontological commitments", but I don't find that
explanation very compelling. Perhaps you can explain why I can't commit to
both "x has type y" and also "x has type z". Interesting
types are those that combine (a la flavors(tm)) with other types without
causing inconsistencies. So I tend to ignore "ontological
commitments" that are not specifically explained within the context of the
first type statement.
JFS> See Thomas
Kuhn's writings about the way science develops. Following is a short, but
useful excerpt: https://cseweb.ucsd.edu/~goguen/courses/275f00/kuhn.html
"Objectivity, Value Judgment, and Theory Choice"
Thanks; I'm reading it now. Thomas Kuhn states:
The oxygen theory, for
example, was universally acknowledged to account for observed weight relations
in chemical reactions, something the phlogiston theory had previously scarcely
attempted to do. But the phlogiston theory, unlike its rival, could account for
the metals' being much more alike than the ores from which they were formed.
One theory thus matched experience better in one area, the other in another. To
choose between them on the basis of accuracy, a scientist would need to decide
the area in which accuracy was more significant.
That twenty-questions method is limited to about one million
entities in the first twenty questions. Since real world ontology is at least
that complex, many more questions would be required to discover the full set of
beliefs. So there are algorithms, at least in principle, which would discover an
individual's ontological belief system.
A more generic algorithm would create questions to ask,
depending on the previous set of answers back to the beginning of the
interview. But it seems to me that making a Q&A system that can ask
questions about objects, events, properties, schedules, logical relationships,
temporal relationships, and many other kinds of things is feasible. That
Q&A system I imagine could ask questions about each or ever situation that
is practiced by some onto in the ontology.
Sincerely,
Rich Cooper,
Rich Cooper,
Chief Technology Officer,
MetaSemantics Corporation
MetaSemantics AT EnglishLogicKernel DOT com
( 9 4 9 ) 5 2 5-5 7 1 2
http://www.EnglishLogicKernel.com
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Thomas
Johnston
Sent: Friday, April 24, 2015 8:41 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine
Learning - ZDNet - 2015.04.10
Surely there are no
algorithms for deriving anyone's ontology. And the best heuristic remains
Quine's: we express our ontological commitments in what we are willing to
quantify over. "There exists an x such that ...." expresses a
commitment to a kind (a universal whose instantiations are particulars), as
well as claiming that there in fact is at least one such instantiation.
On Thursday, April 23, 2015 9:32
PM, Rich Cooper <metasemantics@xxxxxxxxxxxxxxxxxxxxxx> wrote:
Now that there are three of
us, we have a group that subscribes to the belief that ontology is a
mathematical description of an individual's known types of entities, plus each
one's potential behaviors. Our differences seem to be whether the
ontology is generated through an individual subjective aggregation of
experience, or whether the ontology is generated in some more widespread, objectively
understood way.
The issue seems to be how can
we compute that ontology given that the individual is available for
(nondestructive) reverse engineering. If we can take what we know of
ontology in the abstract, and find its wiggles, perhaps we can learn to predict
the wiggles and then simulate ontologeny (!) processes versus the more well
known ontogeny processes. There may be similar underlying descriptions we
can mathematize.
So how can we compute an
individual's ontology? Algorithms anyone?
Chief Technology Officer,
MetaSemantics Corporation
MetaSemantics AT
EnglishLogicKernel DOT com
http://www.EnglishLogicKernel.com
From:
ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx]
On Behalf Of Hans Polzer
Sent: Thursday, April 23, 2015 4:16 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine
Learning - ZDNet - 2015.04.10
I don’t have much to add to
this dialog, but would observe that we should “embrace” diversity – and deal
with that diversity, rather than suppress it. I’m not sure that encouraging
growing diversity is always good – I think that’s how speciation occurs. My own
belief is that we should discourage casual diversity – diversity for the sake
of diversity or out of ignorance of what others have done. I will admit that
sometimes that ignorance leads to positive innovation, but it also leads to
“frictional losses”, to bring physics back into the discussion a bit.
Regarding the use of the term
commonality, I’d like to point out that it requires some implicit understanding
of the types of differences and the extent of such differences across which the
thing in questions is “common”. However, we rarely see anyone using the term
“common” to specify the differences across which something is common.
From:
ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Rich Cooper
Sent: Thursday, April 23, 2015 5:57 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine
Learning - ZDNet - 2015.04.10
RS>How does math or logic
help us all with different philosophic and linguistic backgrounds to help
converge towards universal understanding?
To me, it seems that math or
logic DOES NOT help us all to ... converge towards ... understanding.
Neither math nor logic helps us to understand the same things because we do not
have the same experiences in our memories.
RS> Can
ontologies, being based on logic help us better understand neural world and
mind-brain puzzle?
Math and logic are linear in
the sense that we can use those tools to predict our near term future, or to
chart the probabilities of different outcomes, and otherwise tell us something
about the future given the current and the past.
But people are dynamically
structured, in the sense that we modify our behaviors to accomplish our
individual goals. Feedback control systems do the same thing for
relatively simple mathematical structures, but again they are linear
extrapolations used to squeeze the knowledge so we can find out where it
leaks.
The best you can say is that
on some occasions, people in close groups converge to using a single word to
denote a very, very simple situation. "War" in the thirties
meant WWI, then long over, not a new threat. But in the forties,
"war" supposedly still meant the same thing to everyone, but the
experiences of people directly involved or affected by war were completely
different than the experiences of those uninvolved and unaffected, or of
Alaskan Inuit, or of Australian aborigines, or of Chinese University
Professors, and many more obvious cases. Each of these groups exist where
the divergence in "understanding" is huge for critical words.
But there are many more cases that are more subtle, where the word is used by
many, but the meaning is very, very different. Hence polysemy evolved to
let the divergence keep diverging.
That is why I prefer to cast
linguistic discussions as two agents learning how to communicate with each
other, instead of casting discussions as a class of identical clones imbibing
the same cool aid dictionary of a universal symbology that none of them fully
understand.
RS> We
may have different philosophies but Newton's laws and classical mechanics go a
long way for scientist and engineers; is this due to experimental verification
of math that is behind them?
Actually, as an electrical
engineer, computer scientist, and systems engineer at various points in my
hectic career, I have NEVER had to use Newton's laws, classical mechanics, or
any of that stuff. I used e(t) = i(t) * z(t) and its imaginary friend in
quadrature for lots of things in signal processing and electronics. I
used Fourier and Yates transforms, control theory, optimal control, directed
graphs, undirected network graphs, and gazillions of other math, but I don't
recall using physics or mechanics for much of anything. I used a lot of
logic in electronic logic design tasks. I used simulation equations for
many representations, but none of that is the most important math in my
history.
Math to model throughput,
response time, multiplexing, logic, security, many other figures of merit
(FOMs) get quite detailed when described in math of various kinds, but it is
almost never completely linear with today's technology. So that kind of
math is far more important to my engineering associates who are not in physical
mechanics, but who use math heap by heap.
And, as JFS said a few emails
ago, even physicists don't agree on all that physics stuff. Look at dark
matter, or cold fusion. Every slight difference among a group of collaborating
physicists creates one or more physicist with diverging opinion from the
essential theories of the remaining group.
So my opinion is that we
necessarily have divergence in opinions for good evolutionary reasons, and we
should ENHANCE that divergence at least until we understand it in full.
All progress has been made through divergent cracks in the infrastructure of
that era's "common thoughts(t)".
RS>
A note on your exhilaration about brain being a wonderful machine, and
certainly hope evolving - how did brain-mind of Mammals evolve, (we know
that Aves also have some superb capabilities) and homo sapiens the best so far
but universe probably (and most likely) has beings
with mind-brain-consciousness billions of light years ahead of us? If we
do not understand inter-species communication, how will we understand
communications - among different alien life (forms)?
We have some small insight
into a few other species, such as the work at Georgia State about primates and
communications lessons learned. There is also work (but I am not familiar
with the details) of communication among wolves, dogs, crows, dolphins,
parrots, whales, and many other species.
But the problem, IMHO, is
that each species in a conversation lacks the basic experiences and neural
wiring of the other species. Researchers call that topic "embodied
intelligence".
I can't hold my breath and
explore the ocean rim like the dolphins do, and they can't operate mechanical
and electronic equipment like I can, nor can Narwhales vote. So our
advances on that front have been really slow, but with new knowledge gradually
accreting on the journal floors.
Sooner or later there will
emerge a pile large enough to bring us new knowledge of other species.
RS>Rich -
I have not given enough thought to the relationship between physics - math
(logic) and philosophy hence the ambiguity. Any clarity would help.
For that question, I am
probably not the best choice. As I pointed out above, I have used physics
very sparingly since college. I consider math and logic to be descriptive
of systems I want to understand, develop, or modify. For that reason it
is useful. But for philosophy, I have seldom found intriguing enough
philosophical questions to interest me. You may get better responses from
Matthew West, or John Sowa, or one of the others who are more interested and
invested in the philosophical details.
Chief Technology Officer,
MetaSemantics Corporation
MetaSemantics AT
EnglishLogicKernel DOT com
Perhaps better choice of
words for "universal understanding" could be "common"
understanding or something else that implies agreement on the concept by many.
What I wanted to convey in
the last sentence of communication was that perhaps there was a way for people
to agree on understanding topics such as Physics. What is Physics? It is
about description of nature of physical universe. Things about mind-brain
and metaphysics are more complex or yet to be developed to the extent to which
some math helps us understand physics today.
We may have different
philosophies but Newton's laws and classical mechanics go a long way for
scientist and engineers; is this due to experimental verification of math that
is behind them?
I am looking at partitioning
some parts of physics where Math can help many of us to agree on the
range of validity. Is it the mathematics (which I presume is based on Logic and
or "imagination" or Concepts) that makes understanding more agreeable
- often backed by measurements / experiments?
Rich - I have not given
enough thought to the relationship between physics - math (logic) and
philosophy hence the ambiguity. Any clarity would help.
A note on your
exhilaration about brain being a wonderful machine, and certainly hope
evolving - how did brain-mind of Mammals evolve, (we know that Aves also
have some superb capabilities) and homo sapiens the best so far but universe
probably (and most likely) has beings with mind-brain-consciousness
billions of light years ahead of us? If we do not understand inter-species
communication, how will we understand communications - among different alien
life (forms)?
Can ontologies, being based
on logic help us better understand neural world and mind-brain puzzle?
Can you describe in much more
vivid detail what you mean by your question:
How does math or logic help
us all with different philosophic and linguistic backgrounds to help
converge towards universal understanding?
Why do you think that
"universal understanding" exists? Perhaps there is only
"individual understanding". How would we be able to detect
cases of "universal understanding" to distinguish them from
"individual understanding"?
In my opinion, we only
converge with the groups of people we interact with on a regular basis.
But we never converge for the sake of converging. There must be an
individual motivator to join a specific group. That motivator tends to be
strong in some people for some groups and the inverse for others. But
there is no good enough history database to really collect actual data on the
hundreds of years of written history behind us. But experiments like that
could be done more easily now.
So we can only sigh at the
lack of history details.
Chief Technology Officer,
MetaSemantics Corporation
MetaSemantics AT
EnglishLogicKernel DOT com
1.
All our recent or useful discoveries and products are based on
engineering which are ultimately dependent on physics approximations. Physics
attempts to include life sciences phenomena but not yet convincingly till we
can synthesize Life reliably! But otherwise physics is attempt at description
of at least non-life matter.
2.
Scientists / Engineers know their models are based on Range
of Validity and approximations related to desired accuracy, deviations from
mean, etc.
3.
Reality and truth get us into the fuzzy areas where knowledge of
how the brain works could help us better define the context or meaning. All
Cosmic skylight (e.g. at night) falling on retina - does it describe reality?
What kind?
o
when individual photons from different sources impinged on retina
but actually originated from different objects at different times some of
which in our local-time may not even exist now.
o
how long after photon entered retina - i.e. to individual
subject's brain processing time?
o
as believed in some philosophies that what appears in senses is
not-real the reality is Only One.Thomas Johnson's description in email thread:
that Being is One (and so an explanation of Being should be one) it goes
earlier to Parmenidian - centuries earlier than 600BC.
o
your earlier comments relating to models of objects perceived by
individual brain and connectionism and including referenced URL- your work with
Majumdar.
4.
Now my Question - How does math or logic help us all with
different philosophic and linguistic backgrounds to help converge
towards universal understanding? At least Physicists understand Relativity
and Symmetry models through mathematical "language"?
On 4/22/2015 2:45 PM, Thomas
Johnston wrote:
> But two theories are not better than one, as regimented attempts
> to understand things. I think the underlying intuition which pushes
> physicists towards a unified theory...
Tom, physics is the *worst* example. Almost nobody ever uses the
most general theories. For any particular example, they *always*
use a special-case approximation that is tailored for that example.
And most of them, even for the same project, are *inconsistent*
with one another.
Physicists have known for over a century that Newtonian physics
is only an approximation, but it is still the most widely used
theory. But even then, there are huge numbers of special cases
of Newtonian mechanics: supersonic fluids; subsonic fluids;
turbulent flow; viscous flow; incompressible fluids (which really
aren't). The biggest examples are the incredible number of
approximations for computing the global weather -- different
versions for multiple levels of the atmosphere, different regions
of the earth, different terrains, geographies, ocean currents,
times of day, seasons of the year, etc., etc., etc...
The total number of widely used approximations is in the thousands.
The number of detailed approximations is in the billions -- every
engineer for every project takes a large number of general-purpose
approximations and specializes them for different parts of the project.
Every large system -- ranging from your cell phone to your car to the
trains, planes, and road systems you use every day -- is based on a
large collection of mutually inconsistent approximations to the basic
laws of physics -- all of which are *known* to be false when pushed
to the limits.
Fundamental principle: The human brain is the most complex natural
system known. It is far more complex than the global weather, the
Large Hadron Collider, or the global collection of all the human
constructions on earth.
Analogy: The Greek theories of the cosmos by the pre-Socratics
are closer to modern physics than any current theory of the brain
is to the way it actually works.
John
Thanks.
Ravi
(Dr. Ravi Sharma)
313 204 1740 Mobile
Thanks.
Ravi
(Dr. Ravi Sharma)
313 204 1740 Mobile
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