And just because I like to reinforce Ed's point that the knowledge engineer
is responsible for determining what are "laws of nature" and what is
"plausible inference" relative to a problem to be addressed, I will point
you to Daniel Kahneman's book "Thinking: Fast and Slow" that should be
required reading for anyone planning to tackle real world problems with
logic.
Jim (01)
-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Barkmeyer,
Edward J
Sent: Monday, June 03, 2013 10:31 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Laws: physical and social (02)
John, (03)
I believe that for making an ontology for a particular purpose, one can
encode a great many 'facts', that are "taken to be true" for the purposes of
reasoning with that ontology for that purpose. Whether those 'facts' are
true in the sense of conforming to "objective reality", if you believe there
is such a thing, is an entirely different matter. In particular, the
knowledge engineer must make a separate judgment as to such an ontology is
appropriate for some other purpose. (04)
Some notes below. (05)
> -----Original Message-----
> From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-
> bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F Sowa
> Sent: Sunday, June 02, 2013 8:12 AM
> To: '[ontolog-forum] '
> Subject: [ontolog-forum] Laws: physical and social
>
> In various notes to Ontolog Forum, I emphasized the importance of laws
> (both physical and social) as a foundation for ontology. I won't go
> into all the details, but I'd like to make a few comments:
>
> 1. Laws of physics provide a more fundamental explanation of many
> properties than the notions of "disposition" or "tendency".
> Physicists, for example, would explain why glass is fragile
> along the following lines:
>
> "Look at the structure of the material and how the atoms and
> molecules are linked to one another. Given that structure
> and the laws of quantum mechanics, you can predict that under
> certain conditions, something made of steel will bend, and
> something of the same shape but made of glass will break." (06)
Actually, predicting physical properties of materials from their crystal
structure did not really become viable until the late 1990s, when physicists
finally learned enough about crystal structure, and even then, the theory
only works for materials whose crystal structure is regular. Many metal
alloys, for example, have irregular crystal structures that depend on many
(uncontrolled) variables in the formation of the alloy. So, while this idea
is appealing, physicists would be careful to say that they can accurately
predict the stress resistance of certain glass structures and certain
steels, but possibly not others. There are several steels that will shatter
at temperatures near 0 degrees Kelvin, for example. And the aircraft that
hit the World Trade Center became a 500 knot "sandstorm" of aluminum
particles in seconds. So, your example "laws" could probably be used to
draw appropriate conclusions for common building materials under typical
usage conditions, but would be
inappropriate for tornados or battlefield conditions. This is the danger. (07)
> 2. Many people have found the term 'disposition' to be useful in
> defining terms in an ontology. I have no objection to using
> those terms to simplify an explanation. But I would *not*
> treat dispositions as fundamental. The word 'disposition' is
> just a shorthand way of saying that there exists a law that
> makes a certain kind of prediction.
> (08)
I fully agree, for what that is worth... (09)
> 3. For the social sciences, the interactions are far more complex
> than in physics. But there are regularities that can be used to
> make predictions that have a high probability of being correct. (010)
Aye, and there's the rub. You are now talking about Bayesian inferences,
which is significantly different from "common logic" and what most of us
think of as "ontologies". Most of these social examples relate to "business
rules", rather than "axioms". A "business rule" can be "violated" (fail to
hold), without creating an inconsistency in the knowledge base. And some
important uses of knowledge engineering are diagnostic -- the object is to
detect anomalies in the sensed/measured environment that, whilst being taken
as true, are still in violation of the "laws of conduct". Drivers do veer
across the centerline, and your 2013 Mercedes may be one of those that is
engineered to take evasive action automatically when that happens. I
suspect you can find similar examples in forensic uses of ontology. (011)
As I said, I don't disagree that you can make an ontology that assumes these
rules as axioms, but you have to know that the assumption is not detrimental
to the purpose of the ontology. (012)
> For example:
>
> a) If you go to a store and pay the asking price for an item,
> the sales clerk will take the money and give you the item.
>
> b) If you drive on a highway and stay on the designated side
> of the road, other drivers will stay on their side and
> avoid hitting you or your car.
>
> c) If you work for a company and repeatedly fail to do what
> your manager asks you to do, you will be fired.
>
> For reasoning about social interactions, the laws aren't as strict as
> the laws of physics, but game theory has proved to be useful. (013)
Since about 1960, as I recall. But game theory is a particular mathematical
method based on the idea of optimizing a 'cost function', which is a pure
abstraction on the same level as 'disposition'. (014)
> Following is a survey article from the _Scientific American_:
>
> http://www.ped.fas.harvard.edu/people/faculty/publications_nowak/SciA
> m02.pdf
> The economics of fair play
>
> Following is an influential book on the subject:
>
> Axelrod, Robert (1984) _The Evolution of Cooperation_,
> New York: Basic Books. Revised edition, Perseus Books, 2006.
>
> It's significant that Richard Dawkins, who wrote the book _The Selfish
> Gene_, wrote a highly favorable forward to the revised edition of
Axelrod's book.
>
> I'm happy to see that Dawkins endorses Axelrod's book, but I remain
> skeptical about the memes that Dawkins proposes.
>
> For more info about related issues, see Axelrod's home page:
>
> http://www-personal.umich.edu/~axe/
>
> I followed some of those links to a review of Daniel Dennet's book,
> _Darwin's Dangerous Idea_ by H. Allen Orr:
>
> http://bostonreview.net/BR21.3/Orr.html
>
> From the concluding section of the review:
>
> HAO
> > Although he has produced a provocative and intermittently
> > entertaining book, Dennett's chief claim is unconvincing.
> > Darwinism may have little to tell us outside of biology.
>
> I strongly agree with that last line. I also agree with Orr's
> criticisms of Dennet's version of memes.
>
> In summary, I believe that laws of nature and social behavior are a
> better foundation for ontology than dispositions. I would also
> recommend game theory as a useful methodology for reasoning about social
behavior. (015)
I agree with the first sentence, but with all the caveats above. We have
theories that are based on observations and that are accepted because they
produce predictions that have been verified by experiment. We can therefore
take these theoretical characterizations to be 'true' laws of behavior, for
the purpose of reasoning about a particular class of situations, as long as
that assumption is not seriously harmful to our purposes when it proves to
be an oversimplification. (016)
I don't understand the relevance of game theory (or Bayesian inference) to
"foundation for ontology". Many different mathematical methods were
developed as a means of reasoning about the world, by making models of the
world that are fundamentally different from one another. We have come to
understand that some of them are very good models of natural phenomena, and
lead to correct predictions of natural phenomena. And others are excellent
predictors of social phenomena, on some scale. Game theory is one such
mathematical method; formal inference is another. A game theoretic model of
a social interaction and an axiomatic model of a social interaction are
radically different models. (The axiomatic model -- the "ontology" -- is
the primary subject of this forum.) If the game theoretic model does not
have a 'saddle point', the optimal game theoretic solution is a mixed
strategy: When X happens, do Y 60% of the time, and do Z 40% of the time
(randomly). (That is how hedge funds work.) Axiomatically, that reads,
ifX then What?. As I remember, one suggestion was IF X AND the second hand
on your watch is 0-35, then Y. If X and the second hand on your watch is
beyond 35 then Z. I don't deny that game theory has its place; I just
wonder how it relates to "ontologies", as distinct from philosophical
"disposition". (017)
-Ed (018)
> John
>
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