Hi Adrian, we agree completely on this
issue. But let me amplify.
There needs to be more work on finding a
way to estimate when all (most) of the significant facts and rules have been
identified, IMHO. That only works if you consider evidence for a theory versus
evidence against the same theory. Theorem proving algorithms in conceptually
very simple domains such as math and computer science are missing the point of
the SW. They are useful only after all the facts and rules have been
subjectively selected from the available ones.
In my opinion, the human use of the
semantic web will be to develop the factual basis of a theory through automated
assistance in performing observation, theorizing, classification and
experimentation tasks. Given some really simple deductions that humans make in
between eye blinks, the SW can help collect and organize relevant facts and
rules for later human use. But it isn’t the SW that will demonstrate
proof and substance; it’s the subjective evaluation of people authorized
in some process to produce such evaluations.
Producing a proof graph is a nearly trivial
matter in real world applications, such as legal discovery. The long, odd, toy
proofs of math and computer science don’t represent the realities of
deduction as commonly practiced outside of the academic world. It’s the validity
and verification of facts, the consistency of a theory with MOST of the facts
and rules that matters to people who will use the SW.
That makes reasoning inherently
subjective, IMHO. Of course, academics can disdain the realities of the
practical world, and state that some “stupid/careless” person
screwed up “their” proof, but he people still believe their own
proofs not the supposedly objective, mechanical proofs of an algorithm.
Reasoning methods are still in their
infancy. The really deep research to come will be focused on mapping facts and
rules to reality, to subjectivity, and to measurable data. What JFS and others
call “speech acts” needs a lot of work to be usefully integrated
into these frameworks if reasoning is to become truly HAL like in the future.
JMHO,
-Rich
Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT EnglishLogicKernel DOT com
9 4 9 \ 5 2 5 - 5 7 1 2
From:
ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Adrian Walker
Sent: Monday, August 02, 2010
11:50 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] owl2
and cycL/cycML
Hi Rich and All --
Rich, you wrote... negation as failure is
more human like...
Indeed, relational databases, on which much of the world economy runs, use a
form of negation-as-failure -- If Adrian is not in the table of employees of
Englishlogickernel, then he is not an employee of said company.
Just commonsense, really.
Moreover, if you attach English sentences to predicates [1], you can help
nontechnical users to know what's going on by answering the question
"Is Adrian an employee of Englishlogickernel?"
with
"Assuming that the table
lists all the employees, he is not an employee of that company"
Cheers, -- Adrian
[1] Internet Business Logic
A Wiki and SOA Endpoint for Executable Open Vocabulary English Q/A over SQL and
RDF
Online at www.reengineeringllc.com
Shared use is free, and there are no advertisements
Adrian Walker
Reengineering
On Mon, Aug 2, 2010 at 1:54 PM, Rich Cooper <rich@xxxxxxxxxxxxxxxxxxxxxx>
wrote:
Hi Ian,
If the intent of the tool's designers is to mimic human perspectives on
knowledge and logic, then negation as failure is more human like, IMHO, than
any existing alternative. A person with no experience in an area normally
is very skeptical of assertions that can't be proven within his/her database
of factual and structural knowledge, and reaches the same conclusion. I'm
sure you've heard it said that you don't know what you don't know, so you
assume you know everything until proven otherwise.
Another way to look at it is that, within the bounds of evidence, a judge or
juror has no basis for any conclusion that is not consistent with known,
demonstrated facts. It is always possible that other information will
surface in the future, but the rational deduction of the present moment has
to be based on known facts, not on missing information.
One consequence of this result is that it is very hard to convince anyone of
a fact which has no familiarity, in specific or general terms, to them
personally. That is why attorneys and laws depend on known facts.
-Rich
Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT EnglishLogicKernel DOT com
9 4 9 \ 5 2 5 - 5 7 1 2
It is even more tricky
that this. The failure in "negation as failure"
doesn't mean failure of a given algorithm, it means not provably true. There
are many decidable logics with NAF. If we have an incomplete reasoner for
such a logic, we are *still* incorrect if we take failure to return
"True"
as being equivalent to "False", because the failure may simply be a
symptom
of the incompleteness and nothing to do with NAF.
Simple example: I am using a logic in which negation is interpreted as NAF.
I have a simple boolean theory in which negation isn't used and which
entails A(x). I ask if A(x) is entailed. My incomplete (for entailment)
reasoner answers "False". If I treat this as entailing that A(x) is
not
entailed, then I am really incorrect -- nothing to do with NAF.
In fact I think that we would be well advised to strike NAF from the record
-- it's really not helpful in this discussion :-)
Ian
On 2 Aug 2010, at 17:45, Ed Barkmeyer wrote:
>
> Ian Horrocks wrote:
>
>> Regarding my claim that reasoners are typically used in a way that is
actually incorrect, to the best of my knowledge none of the incomplete
reasoners in widespread use in the ontology world even distinguish
"false"
from "don't know" -- whatever question you ask, they will return an
answer.
Thus, in order to be correct, applications would have to treat *every*
"false" answer as "don't know". I don't know of any
application that does
that.
>>
>
> Put another way, it is not incorrect to treat "don't know" as
"false",
> if "negation as failure" is a stated principle of the reasoning
> algorithm. We can state the 'negation as failure' principle
generally
> as "if the assertion cannot be proved from the knowledge base, the
> assertion is taken to be false."
>
> Of course, "proved" means that the reasoning algorithm can
derive a
> proof, which depends on the algorithm actually implemented in the
> engine. As Ian mentioned earlier, this kind of "proof"
implies that the
> nature of the reasoning algorithm is, or incorporates, "model
> construction", which is typical of various kinds of logic programming
> engines, but there are many hybrid algorithms.
>
> -Ed
>
> --
> Edward J. Barkmeyer
Email: edbark@xxxxxxxx
> National Institute of Standards & Technology
> Manufacturing Systems Integration Division
> 100 Bureau Drive,
Stop 8263 Tel: +1
301-975-3528
> Gaithersburg, MD 20899-8263
FAX: +1 301-975-4694
>
> "The opinions expressed above do not reflect consensus of NIST,
> and have not been reviewed by any Government authority."
>
>
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