🚀 go-pugleaf

berleant@ut-sally.UUCP (Dan Berleant) of U. Texas CS Dept., Austin, Texas
writes:

>	Are you saying that the categorical representations are to be
>	nonsymbolic?  The review of human concept representation I recently read
>	(Smith and Medin, Categories and Concepts, 1981) came down... hard on
>	the holistic theory of concept representation... The alternative
>	nonsymbolic approach would be the 'dimensional' one. It seems a
>	strongish statement to say that this would be sufficient, to the
>	exclusion of symbolic properties... However, the metric
>	hypothesis -- that a concept is sufficiently characterized by a point
>	in a multi-dimensional space -- seems wrong, as experiments have shown.

Categorical representations are the representations of purely SENSORY
categories, and I am indeed saying that they are to be NONsymbolic.
Let me also point out that the theory I am putting forward represents
a direct challenge to the Roschian line of category research in which
the book you cite belongs. To put it very briefly, I claim that that
line of experimental and theoretical work is not really investigating
the representations underlying the capacity to categorize at all; it is
only looking at the fine tuning of category judgments. The experiments
are typically not addressing the question of how it is that a device
or organism can successfully categorize the inputs in question in the
first place; instead it examines (1) how QUICKLY or EASILY subjects do it,
(2) how TYPICAL (of the members of the category in question) subjects rate
the inputs to be and (3) what features subjects INTROSPECT that they are
using. This completely bypasses the real question of how anyone or anything
actually manages to accomplish the categorization at all.

Let me quickly add that there is nothing wrong with reaction-time
experiments if they suggest hypotheses about the basic underlying
mechanism, or provide ways of testing them. But in this case -- as in
many others in experimental cognitive psychology -- the basic
mechanisms are bypassed and the focus is on fine-tuning questions
that are beside the point (or premature) -- if, that is, the objective
is to explain how organisms or devices actually manage to generate
successful categorization performance given the inputs in question. As
an exercise, see where the constructs you mention above -- "holistic,"
"dimensional," or "metric" representations -- are likely to get you if
you're actually trying to get a device to categorize, as we do.

There is also an "entry point" problem with this line of research,
which typically looks willy-nilly at higher-order, abstract
categories, as well as "basic level" object categories (an incoherent
concept, in my opinion, except as an arbitrary default level), and
even some sensory categories. But it seems obvious that the question
of how the higher-order categories are represented is dependent on how
the lower-order ones are represented, the abstract ones on the
concrete ones, and perhaps all of these depend on the sensory ones.
Moreover, often the inputs used are members of familiar, overlearned
categories, and the task is a trivial one, not engaging the mechanisms
that were involved in their acquisition. In other experiments,
artificial stimuli are used, but it is not clear how representative
these are of the category acquisition process either.

Finally, and perhaps most important: In bypassing the problem of
categorization capacity itself -- i.e., the problem of how devices
manage to categorize as correctly and successfully as they do, given
the inputs they have encountered -- in favor of its fine tuning, this
line of research has unhelpfully blurred the distinction between the
following: (a) the many all-or-none categories that are the real burden
for an explanatory theory of categorization (a penguin, after all, be it
ever so atypical a bird, and be it ever so time-consuming for us to judge
that it is indeed a bird, is, after all, indeed a bird, and we know
it, and can say so, with 100% accuracy every time, irrespective of
whether we can successfully introspect what features we are using to
say so) and (b) true "graded" categories such as "big," "intelligent,"
etc. Let's face the all-or-none problem before we get fancy...

>	To discuss "invariant features... sufficient to guide reliable
>	categorization" sounds like the "classical" theory (as Smith & Medin
>	call it) of concept representation: Concepts are represented as
>	necessary and sufficient features (i.e., there are defining features,
>	i.e. there is a boolean conjunction of predicates for a concept).  This
>	approach has serious problems, not the least of which is the inability
>	of humans to describe these features for seemingly elementary concepts,
>	like "chair", as Weinstein and others point out. I contend that a
>	boolean function (including ORs as well as ANDs) could work, but that
>	is not what was mentioned. An example might be helpful: A vehicle must
>	have a steering wheel OR handlebars. But to remove the OR by saying,
>	a vehicle must have a means of steering, is to rely on a feature which
>	is symbolic, high level, functional, which I gather we are not allowing.

It certainly is the "classical" theory, but the one with the serious
problems is the fine-tuning approach I just described, not the quite
reasonable assumption that if 100% correct, all-or-none categorization
is possible at all (without magic), then there must be a set of features
in the inputs that is SUFFICIENT to generate it. I of course agree
that disjunctive features are legitimate -- but whoever said they
weren't? That was another red herring introduced by this line of
research. And, as I mentioned, "the inability of humans to describe
these features" is irrelevant. If they could do it, they'd be
cognitive modelers! We must INFER what features they're using to
categorize successfully; nothing guarantees they can tell us.

(If by "Weinstein" you mean "Wittgenstein" on "games," etc., I have to remind
you that Wittgenstein did not have the contemporary burden of speaking
in terms of internal mechanisms a device would have to have in order to
categorize successfully. Otherwise he would have had to admit that
"games" are either (i) an all-or-none category, i.e., there is a "right" or
"wrong" of the matter, and we are able to sort accordingly, whether or
not we can introspect the basis of our correct sorting, or (ii) "games"
are truly a fuzzy category, in which membership is arbitrary,
uncertain, or a matter of degree. But if the latter, then games are
simply not representative of the garden-variety all-or-none
categorization capacity that we exercise when we categorize most
objects, such as chairs, tables, birds. And again, there's nothing
whatsoever wrong with disjunctive features.)

Finally, it is not that we are not "allowing" higher-order symbolically
described features. They are the goal of the whole grounding project.
But the approach I am advocating requires that symbolic descriptions
be composed of primitive symbols which are in turn the labels of sensory
categories, grounded in nonsymbolic (iconic and categorical) representations.

>	[Concerning model-theoretic "grounding":] The more statements
>	you have (that you wish to be deemed correct), the more the possible
>	meanings of the terms will be constrained. To illustrate, consider
>	the statement FISH SWIM. Think of the terms FISH and SWIM as variables
>	with no predetermined meaning -- so that FISH SWIM is just another way
>	of writing A B. What variable bindings satisfy this?  Well, many do...
>	Now consider the statement FISH LIVE, where FISH and LIVE are variables.
>	Now there are two statements to be satisfied. The assignment to the
>	variable LIVE restricts the possible assignments to the variable SWIM...
>	Of course, we have many many statements in our minds that must be
>	simultaneously satisfied, so the possible meanings that each word name
>	can be assigned is correspondingly restricted. Could the restrictions be
>	sufficient to require such a small amount of ambiguity that the word
>	names could be said to have intrinsic meaning?...  footnote: This
>	leaves unanswered the question of how the meanings themselves are
>	grounded. Non-symbolically, seems to be the gist of the discussion,
>	in which case logic would be useless for that task even in an
>	"in principle" capacity since the stuff of logic is symbols.

I agree that there are constraints on the correlations of symbols in a
natural language, and that the degrees of freedom probably shrink, in
a sense, as the text grows. That is probably the basis of successful
cryptography. But I still think (and you appear to agree) that even if
the degrees of freedom are close to zero for a natural language's
symbol combinatons and their interpretations, this still leaves the
grounding problem intact: How are the symbols connected to their
referents? And what justifies our interpretation of their meanings?
With true cryptography, the decryption of the symbols of the unknown
language is always grounded in the meanings of the symbols of a known
language, which are in turn grounded in our heads, and their
understanding of the symbols and their relation to the world. But
that's the standard DERIVED meaning scenario, and for cognitive
modeling we need INTRINSICALLY grounded symbols. (I do believe,
though, that the degrees-of-freedom constraint on symbol combinations
does cut somewhat into Quine's claims about the indeterminacy of
radical translation, and ESPECIALLY for an intrinsically grounded
symbol system.)
-- 

Stevan Harnad                                  (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard}  !princeton!mind!harnad
harnad%mind@princeton.csnet       harnad@mind.Princeton.EDU