Learning facts in ACT

[Richard M Young]

ACTors:

I have an embarrassingly simple question, or set of related questions,
about fact-learning in ACT.  For the purpose of clarity, I'll pose the
question in the context of learning a set of paired-associates, although I
think the point is more general.  I suspect the answer already exists in a
model somewhere, and I just need to be pointed to it.

Let's take as a starting point the (obviously over-simplified) model of
paired-associate learning and retrieval in the file "paired associate" in
Unit 6 of the ACT tutorial.  The crucial part is two rules (there are only
three anyway), one of which retrieves the "pair" if it can, and if it can't
the other comes into play and "studies" the pair as it is presented.  As is
pointed out in the tutorial, the retrieval rule serves to reinforce the
activation of the pair twice, once because it is retrieved on the LHS of
the rule, and once more when the pair is re-formed from being popped from
the goalstack on the RHS.  Notice that "studying" only boosts the
activation of the pair once, when it is formed (or re-formed) on the RHS.

I got to wondering what would happen if the modelled S ever got into
its/his/her head an INCORRECT pair, i.e. with a valid stimulus paired with
an incorrect response.  As the model stands, the error would never be
corrected, because the erroneous chunk would repeatedly be retrieved, and
would be reinforced (twice) each time.  However, it is probably unrealistic
to suppose that S doesn't read the feedback just because a response has
been retrieved, so there is the opportunity to notice that the retrieved
response is wrong and to "study" the correct response.  However, each time
that happens, the erroneous chunk gets reinforced twice but the correct
chunk only once, as we have seen.  So, given that the erroneous chunks
starts off more active than the correct one, except for a vanishingly low
probability sequence of events, the correct chunk would never get learned
to the point of being retrieved.

OK, so it's a crazily over-simplified model, but it does raise the question
of how *would* ACT learn paired associates given that it starts off with,
or at any stage acquires, erroneous pairs?  I've thought of a couple of
ways, but I'm not even sure they'd really work, and they certainly don't
seem like convincing stories:

(1) Because a retrieval is not guaranteed to be correct, it should not
automatically be popped on the RHS of a retrieval rule.  If the model waits
for feedback and makes sure it pops only a correct pair, then a correct
chunk will be reinforced (once) on each trial.  Unfortunately, the
erroneous chunk also gets reinforced once, by being retrieved on the LHS.
Because the correct chunk is reinforced AFTER the erroneous one, it profits
from recency, and I suppose it's possible that with patience and some luck
with the noise, on some occasion the two chunks will be close enough in
activation that the correct pair gets retrieved and therefore twice
reinforced, and thereafter is likely to win.  But the story doesn't sound
convincing.  (And solutions which involve the repeated, deliberate,
multiple rehearsal of the correct chunk sound too contrived.)

(2) When an erroneous retrieval occurs, and the model discovers that it's
wrong from the feedback, as well as learning a correct pair it could also
learn the incorrect pair with an additional annotation (attribute) of
"wrong".  The retrieval would need to become more elaborate: after
retrieving a pair in reply to a probe with the stimulus, the model would
check whether it could also retrieve an extended pair marked wrong using
the stimulus and the retrieved response.  If it couldn't, OK.  If it could,
then it would need to retrieve another pair, with the previous response
explicitly negated.  (I think that's possible).  Well, maybe, but again it
seems rather contrived.

Can anyone tell me how this is done better?

-- Richard