The Newell Test
You might say this is a soonest, vacuum airport an unwilling calculation of sorts.
That would be a really weird thing to say, though.
Connectionism
Grading
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Earlier Version used grades
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I had a problem with this
If an A is human, where does any
model really belong
New rankings are less
Flexible Behavior
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Computationally Universal
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But some things are easier than others
Real Time
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2 Meanings
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Model makes accurate predictions of
time human processes and learning
take
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Slow learning in connectionist networks
Model does so in a timely manner
Adaptive
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Behaviors serve needs
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Globally is behavior optimal
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Locally, are individual process useful
Vast Knowledge
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Lots of Data
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Not at all well understood how the
brain does this in such a massive
fashion
General mechanism are a bit clearer
Dynamic
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Copes with changes
Knowledge Integration
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Functionality of intellectual
combination
I’d like to call it Representation and
Combination
Newell’s Quote
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“Symbols provide distal access to knowledgebearing structures that are located physically
elsewhere within the system. The requirement
for distal access is a constraint on computing
systems that arises from action always being
physically local, coupled with only a finite
amount of knowledge being encodable within a
finite volume of space, coupled with the human
mind’s containing vast amounts of knowledge.
Hence encoded knowledge must be spread out in
space, whence it must be continually
transported from where it is stored to where
processing requires it. Symbols are the means
that accomplish the required distal access.”
(Newell, 1990, p. 427)
Dictionary
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symbol
noun [C]
a sign, shape or object which is
used to represent something else
What is a Symbol
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Hot Debate in Cognitive Psychology
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Most with an opinion in the class believed the
brain could not contain symbols
I found this astounding until I found out
they were using Newell’s definition
Does a spring symbolize the pressure put
upon it?
Many think symbols could not exist in the
brain by Newell's definition
However, they will all agree the brain
represents the data…
Natural Language
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Can it talk
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Connectionism tries to build the
capability from scratch
ACT-R relies on symbolic interaction to
explain linguistic results
Consciousness
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Can it inspect it’s buffers?
Worse/worse
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I disagree and think ACT-R is better
than worse
In my opinion consciousness is the
parallel matching of all productions
with buffer contents
Learning
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Squire
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Episodic
Semantic
Skills
Priming
Conditioning
Learning is in some ways
fundamental to cognitive
psychology so has been a big focus
Development
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Does it grow
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ACT-R is better than worse I think
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Example in the paper
Bootstrapping problem
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Everything is hand coded just about
Evolution
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Is it susceptible to selection and
variation
Brain
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How do the neurons do it?
Spur to Progress
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Attack of the killer bees is thwarted
Makes reflection on the strengths of
other work better
Interesting compromise
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Theories coming closer
Thad Polk’s Idea (one of Newell’s
Grad Students)
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Production rule compiler
Transforms production rules into
networks
Joe
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Overall I found the article to be
fairly clear and interesting.
However, I was a little fuzzy on the
topic of ACT-RN. I'm not sure I
understand how the chunks are
actually represented, and how the
headers interact with the chunks.
ACT-RN Declarative memories
3
Winner take all
Network
retrieval
chunks
1
4
header
2
slots
5
Represents
chunk name
Figure 1: Type Memories
Ian
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I'm going to work with this analogy:
that an assembler is to a processor
as activations and connection
strengths are to neurons, and that c
is to assembler as act-r is to
activations and connection
strengths, except there isn't the
same layer of abstraction between c
and asm.
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OK
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Er, it turns out I won't reference
that last sentence at all. Here's the
question I have now: how does actr account for individual differences
in cognition? It is nice that the
averages of human data correspond
to act-r data, but it seems that a
fundamental layer of
paramaterization must take place to
account for individual differences.
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Good question. ACT-R actually has
a number of parameters that might
account for individual differences
including W, s, d, tau, and others
less commonly changed such as the
50 ms cycle time…
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The general nature of act-r, with its
emphasis on non-parameterization, also
leads me to a related question. It seems
that much of the body of knowledge on
neuropsychology has come from studies
of partially impaired animals. Is there
any way act-r can account for the
particular ways in which an individual
might deviate from the averaging of
humans.
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We haven’t started to talk about all
the parameters yet. And yes, these
parameters might account for
neuropsychological deficits
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One more, actually. Does anything
like act-r exist for animals? As an
assembler is to a processor, another
assembler is to another processor,
and it seems similar principles may
apply.
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Sure, but I’m not aware any ACT-R
researchers or anyone has used
production rule modeling for
animals…
John?
Dana
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The concept of setting criteria to which all
theories of cognition should aspire to fulfill seems
to be an advantageous goal that would provide
both a way to compare extremely different
theories and to assess their respective strengths
and weaknesses. However several questions
about the validity of the whole process must be
overcome. Since the criteria originated from a
symbolic view, are they biased from the
beginning? Also, will it be possible to convince
everyone that these criteria are the best criteria
to evaluate cognitive theories? No matter how
well defined the rules of the game, if no one
wants to play, it doesn't matter.
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Sure, they are biased, but I’d be happy to
hear their critereon.
In general, the idea of a unified
architecture is an idea that stems from
production system modeling. Many do
not necessarily agree that the idea is
profitable, necessary, etc…
I get the feeling many connectionists just
use connectionism as a tool and aren’t
interested in this unified archtecture
concept… Some however, would agree
that many of these criterea are important
Jane
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why does connectionism do better
on natural languages than actr?
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Because it doesn’t need to be
engineered to pick up on statistics
in the environment… It does so
automatically…
Matt
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"Among other domains for which
ACT-R seems to be lacking
adequate mechanisms are...
emotion and motivation" (p. 20)
What would such a model look like?
Some theories of learning
emphasise motivation. How would it
interact with learning mechanisms
in ACT-R?
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Well perhaps motivations would be
kinda like productions that fired
when certain drive or emotional
states were active
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A general curiosity of mine, which led me
to learn more about ACT-R: "Sometimes
the suspicion is stated that ACT-R is a
general computational system that can be
programmed to do anything." (p. 19) The
four limitations described help me to see
that this isn't true. However, I'd like to
know what makes ACT-R especially suited
to creating accurate cognitive models.
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Hmm… What exactly do you mean?
It is suited for cognitive modeling
because that is what it was
designed to do from the very start
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Inspired by the discussion on
development (p. 26): How would
along-term "metamodel,"
encompassing possibly long term
memory, or a daily juggling of
various priorities interact with ACTR?
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Once we cover the production
competition I think this will be
imaginable… I think perhaps highlevel priorities might be juggled in a
similar fashion according to their
“emotional” utility
This sort of high level modeling
would be fantastically complex
David
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The question that still sticks with
me is how the Newell test is
intended to solve the listed
problems Newell saw in the field, if
that is in fact the intention. For
example, none of the criteria
address the stability or diversity of
theories.
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I think the idea is that by having a
unified model stability is fostered
and diversity is unified.