[ACT-R-users] Need for Multi-Level Activation Spread in ACT-R

[db30 at andrew.cmu.edu]

I'm not sure exactly what you're looking for, but are the existing
hooks for the spreading activation mechanism insufficient for trying
out something else?

There is no constraint that chunks must have a direct association
for there to be an Sji between them.  They only get one by default if
there is, but one can be set explicitly between arbitrary chunks using
the set-sji command or by using the :sji-hook if you want to compute the
values on the fly instead of in advance.

If that doesn't work, then you can also just replace the entire
spreading activation mechanism by using the :spreading-hook parameter
if you want something completely different.  That hook will short
circuit the whole spreading computation and let you return any value
to add into the activation of the chunk without affecting the other
components of the activation equation.

To go along with the declarative hooks, it's also possible to add extra
parameters to chunks to hold any additional information you might need
with the extend-chunks command.  So, you could keep tables of connections
or other data you need without having to store it in slots of chunks.

I think those hooks and commands provide a fair amount of flexibility for
experimenting with new or modified mechanisms, but if there's something
else you feel is necessary let me know.

Dan

--On Monday, September 14, 2009 1:45 PM -0400 "Ball, Jerry T Civ USAF AFMC 
711 HPW/RHAC" <Jerry.Ball at mesa.afmc.af.mil> wrote:

>
>
> We are in the process of mapping the linguistics representations that are
> generated by our language comprehension model into a situation model
> based semantic representation. We are trying to do this in a
> representationally reasonable way within the ACT-R architecture. The
> problem we face is the many-to-many mapping between words and concepts.
> Individual words may map to multiple concepts, and individual concepts
> may may to multiple words. Given this many-to-many mapping, we would like
> to use mapping chunks to map from words to concepts. The mapping chunks
> would encode a single mapping relationship (e.g. a separate mapping chunk
> to map from the word "bank" to the financial institution concept; from
> the word "bank" to the river bank concept; from the concept dog to the
> word "dog"; from the concept dog to the word "canine"). When processing a
> word, the goal is to retrieve the contextually relevant concept. We would
> like to accomplish this in a single retrieval, however, we do not know
> how to do this given the single-level activation spreading mechanism in
> ACT-R. Since there is no direct link between a word and a concept if
> mapping chunks are used (i.e. there is no slot in the concept that
> contains the word), the word will not spread activation to the concept.
> Instead, given the use of mapping chunks, it appears that two retrievals
> are needed: 1) given the word, retrieve a mapping chunk, and 2) given a
> mapping chunk, retrieve a concept. Since our model of language
> comprehension is already slower than humans at processing language, any
> extra retrievals are problematic. In fact, we have already eliminated an
> extra retrieval in determining the part-of-speech of a word. Previously,
> two retrievals were needed: 1) retrieve the word corresponding to the
> perceptual input, and 2) given the word (and context) retrieve the
> part-of-speech of the word. While we were successful in eliminating a
> retrieval, the resulting word-pos chunks contain a mixture of word form
> information (e.g. the letters and trigrams in the word) and pos
> information. Even so, they do not yet contain any representation of
> phonetic, phonemic, syllabic or morphemic information. With just letter
> and trigram information, long words contain many slots. Ideally, we would
> like to represent letter and trigram information independently of each
> other and POS information (allowing them to interact in retrieving a
> word), but given the single-level activation spreading mechanism in ACT-R
> doing so would necessitate multiple independent retrievals, which would
> fail to capture the interaction of letter and trigram information that
> leads to successful retrievals of words in the face of variability in the
> perceptual form (e.g. "arispeed" should retrieve "airspeed").
>
>
>
>       The fall back for mapping words to concepts is to embed all the
> possible concepts as slot values in a word and vice versa. While we
> consider this a representationally problematic solution -- word and
> concept chunks will wind up needing many extra slots, we do not know how
> else to work around the single-level activation spread in ACT-R.
>
>
>
>       The primary empirical argument against the need for multi-level
> activation spread in ACT-R is based on studies which show no activation
> from words like "bull" to words like "milk", even though "bull" activates
> "cow" and "cow" activates "milk". Even if it is true that there are no
> instances of "indirect" activation from "bull" to "milk", this does not
> rule out the need for multi-level activation spread. There is a hidden
> assumption that "cow" and "bull" are directly associated, and that "cow"
> and "milk" are also directly associated. Such direct associations may
> seem reasonable in small-scale models addressing specific spreading
> activation phenomena, but they are questionable in a larger-scale model.
> Do we really want to include all the direct associates of "cow" as slot
> values in the "cow" chunk, and do the same for all other chunks?
>
>
>
>       We understand that the inclusion of a multi-level activation
> spreading mechanism in ACT-R would be computationally explosive. However,
> we would like to have the capability to explore use of such a mechanism
> and to look for ways to keep it computationally tractable. We have
> already dealt with the problem of computational explosion in our word
> retrieval mechanism. Originally, we attempted to use a "soft constraint"
> retrieval mechanism for words. All words in DM were candidates for
> retrieval--the most highly activated word being retrieved. With just 2500
> words in DM, the activation calculations slowed the model down
> considerably. To manage retrievals in a tractable manner we implemented a
> disjunctive retrieval capability combined with a new perceptual span
> mechanism -- the model first tries a hard-constraint retrieval on the
> entire perceptual span (which is larger than a word) using the
> "get-chunk" function (and chop-string under the covers). If get-chunk
> succeeds (indicating that there is a chunk in DM corresponding to the
> entire perceptual span) a retrieval is constructed using the entire
> perceptual span as a hard constraint to retrieve the corresponding
> multi-word unit in DM, if this fails, the model backs-off and uses the
> first space delimited word (using chop-string) in the perceptual span to
> check for a corresponding word in DM -- if a match is found with
> get-chunk, a retrieval is constructed to retrieve the word. If all else
> fails, we construct a retrieval that imposes a hard constraint on the
> first letter (this is less than ideal, but a reasonable compromise). The
> overall effect is a (nearly) soft-constraint retrieval implemented in a
> computationally tractable way.
>
>
>
>       A similar capability to effect multi-level activation spread in a
> computationally tractable manner would be highly desirable.
>
>
>
> Jerry
>
>