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Re: [ontolog-forum] Fruit fly emotions mimic human emotions - ontology d

To: "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Bruce Schuman" <bruceschuman@xxxxxxx>
Date: Mon, 25 May 2015 16:39:55 -0700
Message-id: <002801d09744$1a9224e0$4fb66ea0$@net>

> That wrangling led to single-paradigm systems, which are very strong on one type of problem and useless for anything else.

 

It seems there is profound need for a something like a totally new model of what this entire undertaking is about --

 

That recognizes from square one that this subject is "absolutely interdisciplinary" -- recognizing that the spectrum of legitimate human inquiry is very broad, but still one spectrum -- that the arrangement of "departments" in just about any university begins to illustrate the elements of that spectrum...

 

The categories in any major library system also illustrate the elements of that spectrum -- and indeed, ARE arranged in a linear order like a spectrum -- with little "in-between" spaces to fit in new stuff, like interdisciplinary/hybrid categories….

 

Today, it seems we are trying to develop a universal ontology by patching together particular ontologies from particular disciplines and silos -- no doubt a worthy endeavor.  Can that process be generalized or universalized in some way?  Is there some primal interpretive lingua-franca that can derive the entire subject from a fundamental compositional primitive -- some fundamental unit of information that can not only construct and interpret all knowledge -- but interconnect all knowledge -- across the existing spaces between the disciplines and departments ???  Between "the sciences" and "the humanities" ????  Between general theories and the particular data they interpret?

 

Today, I've been looking at an introductory book called "Applied Ontology" out there in a very clean PDF, suggested by someone on ontolog.  It's written by philosophers and offers what might seen to be a naïve ambition on its back cover -- reaching for this "integral" ontology that can interconnect processes and sectors...

 

“Ontology is the philosophical discipline which aims to understand how things in the world are divided into categories and how these categories are related together. This is exactly what information scientists aim for in creating structured, automated representations, called 'ontologies,' for managing information in fields such as science, government, industry, and healthcare. Currently, these systems are designed in a variety of different ways, so they cannot share data with one another. They are often idiosyncratically structured, accessible only to those who created them, and unable to serve as inputs for automated reasoning. This volume shows, in a nontechnical way and using examples from medicine and biology, how the rigorous application of theories and insights from philosophical ontology can improve the ontologies upon which information management depends.”

 

http://ontology.buffalo.edu/AppliedOntology.pdf

 

“Databases and other systems for storing particular information should be able to provide empirical data for testing general theories, and the general information contained in controlled vocabularies and their ilk should, in turn, provide sources of reference for empirical researchers and clinicians. How better, for example, to form and test a theory about pneumonia than by culling the clinical records of every hospital which has recorded cases of it? How better to prepare for a possible epidemic than by linking the electronic record systems of every hospital in the country to a centralized source, and then programming that source to automatically tag any possibly dangerous trends?

 

“But in order for these goals to be realized, automated information systems must be able to share information. If this is to be possible, every system has to represent this information in the same way. For any automated information system to serve as a repository for the information gathered by researchers, it must be pre-programmed in a way that enables it to accommodate this information. This means that, for each type of input an information system might receive, it must have a category corresponding to that type. Therefore, an automated information system must have a categorial structure readymade for slotting each bit of information programmed into it under the appropriate heading. That structure, ideally, will match the structure of other information systems, to facilitate the sharing of information among them. But if this is to be possible, there must be one categorial structure that is common to all information systems. What should that structure look like?

 

> Recommendation in micai.pdf:  Implement various theories.  Test them alone and in different combinations.  See what works.  Collaborate!

 

Collaboration is a “unity-in-diversity” process that brings together different perspectives to work on something held in common.   Yes, specifics are often highly incommensurate – and patching together databases from alternative schematics can get crazy-impossible.  But human beings in a context of mutual respect have a capacity for empathic interpretation that opens new insights into semantics – that shows us how people CAN understand one another, even when it is true that time flies like an arrow, fruit flies like bananas, and we can time skiers like sprinters.

 

Maybe we need a collaborative ontological fan-in engine that absorbs input from every school of thought and hammers on the specifics until a universal frame appears.

 

- Bruce Schuman

Santa Barbara

 

 

 

 

 

-----Original Message-----

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F Sowa

Sent: Monday, May 25, 2015 1:30 PM

To: ontolog-forum@xxxxxxxxxxxxxxxx

Subject: Re: [ontolog-forum] Fruit fly emotions mimic human emotions - ontology discovery possible?

 

Tom,

 

I am well aware of those debates and of the intensity on all sides:

 

> This is the “vs.” I am referring to, and in spite of your “should”,

> the facts on the current ground is that there is this debate. Indeed,

> the article by Fodor and Lepore and the reply by David Chalmers, both

> of which you recently provided links to, make it quite clear how

> intense the “vs.” remains.

 

The most cutthroat debates are among philosophers and theologians -- primarily because they're searching for certainty, and they have no way of knowing when they're wrong.

 

That was the point of my talk at the Mexican AI conference in November:

 

    http://www.jfsowa.com/talks/micai.pdf

    Why has AI failed?  And how can it succeed?

 

That wrangling led to single-paradigm systems, which are very strong on one type of problem and useless for anything else.

 

> Here's Gardenfors, on my "vs.":

> “Within cognitive science, there are currently two dominating

> approaches to the problem of modeling representations.” From the point

> of view of the symbolic approach (which I and others call the “mental

> representation” approach), “cognition is seen as essentially being

> computation, involving symbol manipulation.”

 

I presented a guest lecture at Lund at PG's invitation, so I won't be too harsh on him.  Peter did good work on belief revision, which I strongly recommend.  He's the G of the AGM axioms.  But that quotation is an extremely oversimplified and misleading summary of AI and cognitive science.

 

Marvin Minsky's _Society of Mind_ is a good antidote to that kind of partisanship.  See the reference in Slide 13 of micai.pdf:

http://web.media.mit.edu/~push/CognitiveDiversity.pdf

 

That was a strong influence on my "Flexible Modular System" (FMF):

http://www.jfsowa.com/pubs/arch.pdf

 

A quotation from arch.pdf

> The lack of progress in building general-purpose intelligent systems

> could be explained by several different hypotheses:

> 

>  * Simulating human intelligence on a digital computer is impossible.

> 

>  * The ideal architecture for true AI has not yet been found.

> 

>  * Human intelligence is so flexible that no fixed architecture can do

>    more than simulate a single aspect of what is humanly possible.

> 

> Many people have presented strong, but not completely convincing

> arguments for the first hypothesis.  In the search for an ideal

> architecture, others have implemented a variety of at best partially

> successful designs. The purpose of this paper is to explore the third

> hypothesis:  propose a flexible modular framework that can be tailored

> to an open-ended variety of architectures for different kinds of

> applications.

 

For examples that show how the FMF works, see "Two paradigms are better than one, and multiple paradigms are even better":

http://www.jfsowa.com/pubs/paradigm.pdf

 

Fundamental principle:  Neuroscientists are the first to emphasize that

*nobody* really knows how the brain works.  For philosophers to engage in endless wrangling about the virtues of one half-baked theory or another is fundamentally misguided.

 

Recommendation in micai.pdf:  Implement various theories.  Test them alone and in different combinations.  See what works.  Collaborate!

 

John

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