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<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Hello,</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Since there is not a lot of activity on the ACT-R or Soar mailing list
of late, I thought I would pose some theoretical questions to the community
concerning work we have been doing at our lab to implement ACT-R onto a robot.
We are working with a production system architecture called SS-RICS, which was
inspired by ACT-R, and has much of the same functionality as ACT-R. </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Each paragraph below is meant to be a self-contained set of questions
to ponder, if you want to respond to just one paragraph, please feel free to do
so, you don’t need to read all the paragraphs. Your input would be
appreciated.</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>1) ACT-R grew out of the General Problem Solver (GPS) production
system architecture developed by Newell and Simon. Their intent was to
develop a *general* problem solver using various syntax based strategies.
These are also known as weak method problem solvers in AI. However, it
seems as if ACT-R has moved toward strong method problem solvers, which use *specific*
domain knowledge to solve problems. So the question is, can we develop
ACT-R/Soar models that are general adaptable problem solvers that are NOT
domain specific? Or does domain specificity so influence the problem
solving process, that one cannot extricate oneself from the domain?</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>2) ACT-R is firmly rooted in the “symbolic” side of AI
as opposed to the “distributed” side of AI. A criticism of
traditional symbolic AI is that it tends to be brittle and non-adaptive if the symbols
do not match the current problem space. Is this also true of ACT-R?
If so, does ACT-R seem to be a logical fit for robotics or will it just
introduce the same set of symbolic problems (especially the frame problem) that
are currently found in AI.</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>3) If one considers ACT-R to be “just another symbolic
system”, as some in the AI community do, then what does ACT-R or
computational cognitive psychology have to offer the robotics community?
I have not seen references to memory decay in the AI literature however, most
people in the AI community consider memory decay to be a handicap of the human
cognitive system. While I disagree with that, what other mechanisms/functionality
of the human cognitive system would appear to be the most important additions
to robotic control mechanism that have been overlooked by the AI community?</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>4) There is a distinction in psychological literature between long
term, short term and working memory, but what does that mean
computationally? For us, we have implemented different decay rates for
LTM and STM. However, those decay rates are really part of a continuum of
decay rates for all memories. For example, if we have one million
memories on our robot, don’t those memories form a continuum of various decay
rates? Why should I have to have a place holder for LTM and STM and WM?
Why can’t all my memories just have various decay rates? It seems
as if LTM, STM and WM are simply convenient labels for something that is really
a continuum. If we define WM as those memories currently in use, does
that preclude LTM or STM from the problem space?</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>4) Has there ever been any use of *different* decay rates *within* an
ACT-R model? I am talking about different base level activations for
different chunks at the beginning of the model run. For example, we have
found it very helpful to code perceptual processing as building on lower level
memories that decay very quickly. Once the higher level concepts are
formed, the lower level memories are quickly forgotten, and the higher level
concepts remain. So, the higher level concepts have a slower decay rate
than the lower level perceptions. I know right now, in ACT-R, we request
information from the buffers, but I have been working on some memory research
that says that information will “get in” even if there is not a “request”
for it (or an attentional shift to it). Perhaps this is more of a
statement than a question then; what do people think of having more control
over decay rates for individual chunks, especially those coming in from the
perceptual components?</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>5) The transition from a rule-based, symbolic understanding of a
problem, to a proceduralized, intuitive, understanding of a problem is
difficult to represent computationally. What does proceduralization really
mean? At the symbolic level, we can change latency values, or skip over
rules, to speed up the procedure. But really, psychologically, it seems
as if the symbolic level rules are being “rewritten” or “re-compiled”
as subsymbolic representations. On our robot, it is unclear how we could
take symbolic production systems and recompile them in a subsymbolic way to
produce improved performance seen in humans. </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>6) When does a memory become and memory? When you first perceive
something, is it a memory then or does it become a memory later? Is our
conceptualization of the world a conceptualization of memories or actual
stimuli? Does some level of processing have to take place before it can
be called a memory? For example, with our robot, it sees dots and points
returned from its laser, which are organized into lines. But we struggle with
the idea that the dots and points are also memories. We have buffers similar
to ACT-R, but we ended up having a lot of processing that goes on before
information even gets to the buffer. So that means there is a lot of
information unavailable to the production system. For example, points get
organized into lines which then get organized into shapes at a Gestalt layer,
which then become memories for the production system. So, a lot of processing
goes on before our sensory data becomes a memory. So, again, when does a
memory become a memory? </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>7) Is cognition sensory specific? Much of our code right now for
the robot seems to be for interpreting information the robot gets from each one
of its sensors. So, if we were to put a new sensor on the robot, would it
still be able to make sense of the world? That is a direction we are
going toward, but it can be very difficult. Many of the productions we
end up writing seem to be tied directly to specific sensory stimuli, and it is difficult
to write productions that are general and not tied to sensory information.
So, is cognition bound to the sensory information returned from perceptual mechanisms
(as Rodney Brooks would say) or can it be separated from sensory
information. True, that is what the symbolic level can do, but then, does
the symbolic level become brittle if it is not tied to the sensory layer?</span></font></p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Troy Kelley</span></font></p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>U.S.</span></font> Army Research Laboratory</p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Human Research and Engineering Directorate</span></font></p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>AMSRD-ARL-HR-SE, </span></font>APG, MD</p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>21005-5425</span></font></p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Voice: 410-278-5859</span></font></p>
<p class=MsoAutoSig><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>email: tkelley@arl.army.mil</span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'> </span></font></p>
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