Light

[bever@prodigal.psych.rochester.EDU]

Recent correspondence has focussed on the performance level of the
Rumelhart and McClelland past tense learning model and subsequent models,
under varying conditions of feeding.  Pinker and Prince point out that
the model is unsuccessful by normal statistical standards.  The responses
so far seem to be: (1) that's always the way it is with new models
(Harnad), (2) adults may perform more like the model than P&P assume
(Bates, Elman, McClelland) and (3) children may not conform to the rules
very well either (Bates, Marchman).

We think that the exact performance level and pattern of the model is not
the only test of its validity, for the following reasons:

1) Such models work only insofar as they presuppose rule-based
structures.

2) The past-tense overgeneralization errors are errors of behavior not
knowledge.

Many statistically valid models of phenomena are fundamentally incorrect: 
for example, Ptolomeic astronomy was reputed to be quite accurate for its
day, especially compared with the original Copernican hypothesis.  The
question is, WHY does a model perform the way it does?  We have
demonstrated (Lachter and Bever, 1988; Bever, 1988) that existing
connectionist models learn to simulate rule-governed behavior only
insofar as the relevant structures
are built into the model or the way it is fed.  What would be
important to show is that such models could achieve the same
performance level and characteristics without structures and
feeding schemes which already embody what is to be learned.  At
the moment, insofar as the models succeed statistically, they
confirm the view that language learning presupposes structural
hypotheses on the part of the child, and helpful input from the
world.

The exact performance level and pattern of children or models is
of limited importance for another reason: what is at issue is
linguistic KNOWLEDGE, not language behavior.  There is
considerable evidence that the overgeneralization behavior is a
speech production error, not an error of linguistic knowledge. 
Children explicitly know the difference between the way they say
the past tense of a verb and the way they ought to say it - the
child says 'readed' for the same kind of reason that it says
'puscetti' - overgeneralization in speech production of a
statistically valid property of the language.   Most significant
is the fact that a child knows when an adult teases it by
imitating the way it says such words.   Whatever the success or
failure of an inductive model, it must fail to discover the
distinction between structural knowledge, and language behavior,
a distinction which every child knows, and a distinction which is
vital to understanding both the knowledge and the behavior the
child exhibits.  In failing to make the distinction, the more a
model succeeds at mimicking the behavior, the clearer it becomes
that it does NOT acquire the knowledge.  The view that a bit of
'knowledge' is simply a 'behavioral generalization' taken to an
extreme, begs the question about the representation of the
distinction: insofar as it answers the question at all, it gets
it wrong. 

Connectionist models offer a new way to study the role of
statistically valid generalizations in the acquisition of complex
structures.  For example, such models may facilitate the study of
how structural hypotheses might be confirmed and extended
behaviorally by the data the child receives (Bever, 1988): the
models are potentially exquisite analytic engines which can
detect subtle regularities in the environment, given a particular
representational scheme.  We think this may be their ultimate
contribution to behavioral science.  But they solve the puzzle
about the relationship between structure and behavior no more
than an adding machine tells us about the relationship between
the nature of numbers and how children add and subtract. 

Tom Bever
Joel Lachter

Bever or Lachter @psych.prodigal.rochester.edu



References:

Recent net correspondence between Bates, Elman, Harnad, Marchman,
McClelland, Pinker and Prince.

Bever. T.G., 1988.  The Demons and the Beast - Modular and
Nodular kinds of Knowledge.  University of Rochester Technical
Report, #48; to appear in Georgeopolous, C. and Ishihara, R.
(Eds).  Interdisciplinary approaches to language.  Kluwer,
Dordrecht, in press. 

Lachter J. and Bever, T.G. (1988) The relation between linguistic
structure and associative theories of language learning -- A
constructive critique of some connectionist learning models. 
Cognition, 28, pp 195-247.
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