**Subject: **Re: BISC: A Challenge to Bayesians (augmented version)

**From: **MVCS (*n.o.s.p.a.m.-mvcs@idt.net*)

**Date: **Mon Aug 07 2000 - 17:23:52 MET DST

**sorted by:**[ date ] [ thread ] [ subject ] [ author ]**Next message:**Oscar Duarte: "UNFUZZY 1.2"**Previous message:**cnsthl@barcelona.com: "Ya tengo mi correo @barcelona.com 1876"**Maybe in reply to:**Michelle T. Lin: "BISC: A Challenge to Bayesians (augmented version)"**Next in thread:**Michiel de Roo: "Re: BISC: A Challenge to Bayesians (augmented version)"**Maybe reply:**MVCS: "Re: BISC: A Challenge to Bayesians (augmented version)"

"Michelle T. Lin" <michlin@eecs.berkeley.edu> wrote:

*>....My examples are intended to challenge the unquestioned belief
*

*>within the Bayesian community that probability theory can handle any
*

*>kind of information, including information which is perception-based.
*

I question your assertion. Please provide documentation and cite

sources which prove and demonstrate your assertion.

Please also define what you mean by "handle" and show documentation

and cite sources that prove and demonstrate that your definition is

the same or different than that used "within the Bayesian community".

Alternately, please prove and demonstrate that "the Bayesian

community" is monolithic in "their" intrepretation, application, and

use of the term "handle".

*>However, it is possible -- as sketched in the following -- to
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*>generalize standard probability theory,
*

Please provide a brief definition of what you call "standard

probability theory".

*>PT, in a way that adds to PT a
*

*>capability to operate on perception-based information.
*

*>From the tone of your post, I assume that your statement here is
*

nothing less than global in breadth of application (as in "within the

Bayesian community", and "the unquestioned belief"). Do you not

purport that this "way" is unqualifiably capable of operating on

perception-based information, and that this capability is somehow

intrinsically and inherently different from any/all "ways" that "the

Bayesian community" is capable of handling such information? Or have I

misread your intent?

*>...progression from crisp sets to fuzzy sets,
*

In your opinion this characteristic is unable to be shared or

represented in any way when using Bayesian methods?

*>... In PT+, probabilities, functions,
*

*>relations, measures and everything else are allowed to have fuzzy
*

*>denotations, that is, be a matter of degree.
*

Again, this characteristic is unable to be shared or represented in

any way when using Bayesian methods?

*> In particular,
*

*>probabilities described as low, high, not very high, etc. are
*

*>interpreted as labels of fuzzy subsets of the unit interval or,
*

*>equivalently, as possibility distributions of their numerical values.
*

I've done the same with NNs. And then cast them as Bayesian

structures. Your assertion is inaccurate to the extent that it is

meant to circumscribe a sacred territory germain ONLY to fuzzy set

theory and its applications.

*>... By fuzzy granulation of a variable, X,
*

*>what is meant is a partition of the range of X into fuzzy granules,
*

*>with a granule being a clump of values of X...
*

Again, I've done this in an NN implementation that has a direct

correlary in a Bayesian structure. Your assertion is again inaccurate

if meant to designate an exclusive processing method that can not be

reproduced by Bayesian means.

*>...(c) nl-generalization involves an addition to PT++ of a
*

*>capability to represent the meaning of propositions expressed in a
*

*>natural language,
*

I do this with Bayesian nets all the time. Your assertion is

inaccurate.

*>...In summary, contrary to the central tenet of Bayesian belief,
*

Please define what you mean by "the" central tenet of Bayesian belief

as it supports your assertions, and provide citations that prove and

demonstrate that this is "the" "central tenet" of "the Bayesian

community".

*>... there is a widely held belief that probability theory,
*

*>upgraded or not, is sufficient for dealing with any or all issues
*

*>which relate to partial certainty or incompleteness of information.
*

Please specify. You seem to be jausting with windmills (IMO). You are

indeed becomming aware of the limitations of certain processing

methods and applications which have used certain technologies. But

these limitations are, IMO, to a large degree the fault of the

process, methodology, and implementation of technologies rather than

an inherent flaw of the basic technologies used to embody the

implementation of the concepts.

In other words, I think you are throwing the baby out with the bath

water. IMO, whatever technology works is the one to use. I've seen

perception-based Bayesian applications, and perception-based problems

for which it is obvious that Bayesian methods will not suffice. Same

for FL. Same for NNs. Same for LISP-based technologies. Same for

"traditional" technologies.

BTW, I am a pragmatist.... not a "Bayesian".

Mind & Vision Computer Systems

"Intelligent Processing Systems for the Energy Industry"

_________________________________________________________________

| Jeffrey L. Baldwin |

| Voice/Fax/Data: (972) 238-5503 |

| email: mvcs@idt.net 73051.1316@compuserve.com |

| http://idt.net/~mvcs |

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**Next message:**Oscar Duarte: "UNFUZZY 1.2"**Previous message:**cnsthl@barcelona.com: "Ya tengo mi correo @barcelona.com 1876"**Maybe in reply to:**Michelle T. Lin: "BISC: A Challenge to Bayesians (augmented version)"**Next in thread:**Michiel de Roo: "Re: BISC: A Challenge to Bayesians (augmented version)"**Maybe reply:**MVCS: "Re: BISC: A Challenge to Bayesians (augmented version)"

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