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<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>More generally, whenever a composite
chunk is competing with noncomposite chunks (e.g. words vs. letters, phrases
vs. words, objects vs. features, collections vs. individuals), without carryover
of source activation, the elements of the composite chunk will need to be
retained in the focus of attention to activate the composite chunk given the
current implementation of spreading activation (and assuming retrievals are not
specific to the composite type). So long as composite chunks are limited to a
few slots and values, retaining the noncomposite chunks in the focus of
attention should work to activate the composite chunk. However, carryover
source activation offers an alternative to this approach.</span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'> </span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>I think a composite chunk would be the
best way to handle the problem in the current implementation. And, the problem
of a composite chunk competing with a noncomposite chunk would seem to go away if
the activation levels were higher for composite chunks. For example, after
seeing the group of words, “kicked the bucket” repeatedly, act-r could
create a new chunk for the entire phrase out of separate chunks for each word,
based on activation levels. This could be done at the production system
level, but it would also be interesting to have this as an architectural
feature as well. Anyway, at that point, you could assume a higher level
of activation for the composite chunk, “kicked the bucket”, as
compared to a lower less occurring word like, “gubernatorial”.
Furthermore, spreading activation can be thought of as a computational approach
to context. So, reading a paragraph about someone’s impending
demise would spread activation to phrases like “kicked the bucket”
rather than “kicked the can”.</span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'> </span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>All that being said, I like the idea of
carryover of source activation.</span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>In ACT-R, the activation of a DM
chunk is a combination of the base level activation and the source activation
spread from buffers in the focus of attention. The activation of all DM chunks
(consistent with the retrieval template) is computed (in parallel) at the time
of a retrieval and the most highly activated chunk is retrieved (subject to
noise). It has recently been brought to my attention that there is no carryover
of source activation from DM retrieval to DM retrieval. The source activation
is recomputed on each retrieval given the contents of the buffers at the time
of the retrieval. On the assumption that base level activations reach asymptote
for frequently used DM chunks (following the power law of learning), it is
unclear how base level activation alone can account for recency effects of DM
chunks which have reached asymptote, since changes in base level will be
"in the noise". Something like carryover source activation would
appear to be needed.</span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'> </span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>The asymptotic nature of the activation
equation can be a little problematic given the task. I have been looking
at developing an architecture that has various levels of activation or decay
for different memory chunks within the same model. Basically, some memories
activate or decay much faster than others depending on the type of memory they
are (i.e. perceptual, low level memories decay faster than high level
conceptual memories). This allows some more control over when the memory
reaches asymptotic levels. I have also been looking at using a “return-to-zero”
function, so that once a memory asymptotes, it can be “reset” to
zero depending on the situation. This would simulate the effect of a
low-level neuron which fires, goes through a refractory period (similar to the
asymptotic part of the activation function), then eventually returns to “zero”
where it can then fire again starting from zero. I am not saying that all
memory functions this way, or that memories are the same as neurons firing, but
it is a useful function to have when modeling memory. </span></font></p>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'> </span></font></p>
<div>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>Troy Kelley</span></font></p>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>U.S.</span></font><font color=navy><span
style='color:navy'> Army Research Laboratory</span></font></p>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>Human Research and Engineering Directorate</span></font></p>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>AMSRD-ARL-HR-SE, APG, MD</span></font></p>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>21005-5425</span></font></p>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>Voice: 410-278-5859</span></font></p>
<p class=MsoAutoSig><font size=3 color=navy face="Times New Roman"><span
style='font-size:12.0pt;color:navy'>email: tkelley@arl.army.mil</span></font></p>
</div>
<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'> </span></font></p>
<div>
<div class=MsoNormal align=center style='margin-left:.5in;text-align:center'><font
size=3 face="Times New Roman"><span style='font-size:12.0pt'>
<hr size=2 width="100%" align=center tabindex=-1>
</span></font></div>
<p class=MsoNormal style='margin-left:.5in'><b><font size=2 face=Tahoma><span
style='font-size:10.0pt;font-family:Tahoma;font-weight:bold'>From:</span></font></b><font
size=2 face=Tahoma><span style='font-size:10.0pt;font-family:Tahoma'> act-r-users-bounces@act-r.psy.cmu.edu
[mailto:act-r-users-bounces@act-r.psy.cmu.edu] <b><span style='font-weight:
bold'>On Behalf Of </span></b>Jerry.Ball@mesa.afmc.af.mil<br>
<b><span style='font-weight:bold'>Sent:</span></b> Tuesday, October 25, 2005
2:33 PM<br>
<b><span style='font-weight:bold'>To:</span></b> act-r-users+@andrew.cmu.edu<br>
<b><span style='font-weight:bold'>Subject:</span></b> [ACT-R-users] Spreading
Activation in ACT-R</span></font></p>
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<p class=MsoNormal style='margin-left:.5in'><font size=3 face="Times New Roman"><span
style='font-size:12.0pt'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>In ACT-R, the activation of a DM
chunk is a combination of the base level activation and the source activation
spread from buffers in the focus of attention. The activation of all DM chunks
(consistent with the retrieval template) is computed (in parallel) at the time
of a retrieval and the most highly activated chunk is retrieved (subject to
noise). It has recently been brought to my attention that there is no carryover
of source activation from DM retrieval to DM retrieval. The source activation
is recomputed on each retrieval given the contents of the buffers at the time
of the retrieval. On the assumption that base level activations reach asymptote
for frequently used DM chunks (following the power law of learning), it is
unclear how base level activation alone can account for recency effects of DM
chunks which have reached asymptote, since changes in base level will be
"in the noise". Something like carryover source activation would
appear to be needed.</span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>As a practical example of where
carryover source activation would be useful, considering the recognition of
idiomatic expressions like "kicked the bucket". At the processing of
the word "bucket", recognition of the idiom "kicked the
bucket" instead of just the word "bucket" requires activation
from both "kicked" and "bucket". With carryover source activation,
the activation of "kicked the bucket" by "kicked" would
carryover to the activation of "kicked the bucket" by
"bucket". Without carryover source activation, it will be necessary
for "kicked" to remain in the focus of attention along with
"bucket" in order to spread source activation to "kicked the
bucket". </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>More generally, whenever a composite
chunk is competing with noncomposite chunks (e.g. words vs. letters, phrases
vs. words, objects vs. features, collections vs. individuals), without carryover
of source activation, the elements of the composite chunk will need to be
retained in the focus of attention to activate the composite chunk given the
current implementation of spreading activation (and assuming retrievals are not
specific to the composite type). So long as composite chunks are limited to a
few slots and values, retaining the noncomposite chunks in the focus of
attention should work to activate the composite chunk. However, carryover
source activation offers an alternative to this approach.</span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>Speculating on other potential uses
of carryover source activation, whereas long-term learning would presumably be
reflected in base level activations, short term learning effects might involve
an interaction of base level and carryover source activation. This could
provide an explanation for spacing effects in learning and the discontinuity in
the rate of decay that is often found across short and longer time frames.</span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>Even more speculatively, carryover
source activation might be viewed as residual neural activity akin to
Grossberg's notion of resonance, whereas base level activation results from
long term changes in neural potentiation.</span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'>Jerry</span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
<p class=MsoNormal style='margin-left:.5in'><font size=2 face=Arial><span
style='font-size:10.0pt;font-family:Arial'> </span></font></p>
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