It's probably more "trial and error", but consistent trial and error--which can
be iterative (akin to a search algorithm).
So I view imagination as a combination of coordination (adding inferences) and
mental simulation (supporting diverging viewpoints). According to Piaget,
there is observation (direct sensory perception), and coordination (drawing
inferences from perception an well as other inferences).
So what inferences can we have during coordination? Certainly instance
induction (forming cases), type induction (forming types), concurrence
association, sequence association, similarity creation, difference creation,
equality creation, and analogy which I view as "idea substitution", as well as
other processes. I would lump planning into the coordination bucket as well.
All these things can occur during coordination. And all these coordination
processes are always running in PAM-P2.
Finally, to answer Mike Tinter's question of mental simulation. Daydreaming is
already accounted for in the PAM-P2 architecture.
http://piagetmodeler.tumblr.com
PAM-P2 uses a current model of the world and forward models of the world
(called. "viewpoints"). The forward models are for mental simulation /
daydreaming. Daydreaming is always occurring. The Simulation Supervisor
component controls daydreaming and the Reaction subsystem can interrupt it.
We don't know how the mind works exactly, but we can define requirements. We
know what behavior we want a Cognitive System to exhibit and can build a system
that meets our requirements, however short it falls. Then refine our
requirements to close the gaps with [human] exemplars. A basic spiral
prototyping approach.
~PM.
Date: Tue, 4 Dec 2012 15:08:08 -0500
Subject: Re: [agi] Internal Representation
From: [email protected]
To: [email protected]
We do not need to know exactly how the brain (mind) works. But to say that,
'all we really need are some observable learning events to work from,' is too
simplistic. If the program is intelligent then it is intelligent. Yes of
course. But the interesting questions concern the problem of overcoming those
challenges that we haven't figured out yet. So yes, of course, if your program
produces thought-acts just like a child then you can say that you don't need to
know the details of how a human child's mind is able to work with general
intelligence in order to get your program to work. I agree with that, but the
chance to have that conversation is not why I have been posting in these
groups. It is actually a functional identity hypothesis. I was never truly
interested in the functional identity issues that these discussion groups get
caught up in, I only got caught up in them while trying to get other people to
move on to more interesting discussions. Since a computer is not a living
brain the matter is a priori settled regardless of any divergence of opinion.
The real issue is figuring the internal representations and processes which
could get a program to work. Your experimental methods are commendable, but to
declare that the method is a "simple iterative process," is not an accurate
description of what you actually do. It is like saying that life is just a
simple iterative process. I might use a line like that in poetry or fiction (if
I ever wrote poetry or fiction) but i would not want that to be remembered as
my philosophy of life!
Here is a question I am interested in:How do you or how would you integrate
imagination into the analysis of some simple recognition problem?Jim Bromer
On Tue, Dec 4, 2012 at 12:21 PM, Piaget Modeler <[email protected]>
wrote:
Jim: "If you are curious about my opinions on this I would try to explain it,"
Sure Jim, I'd like to know your thoughts on the subject. Perhaps I'm missing
something.
My point is that we don't really need to know what's under the hood from an
architecturalperspective. The internal representation is an implementation
detail, if you think of the
larger functional processes as black boxes with specific inputs and outputs and
well defined behavior.
I have a straw man representation which I am experimenting with. If it's
adequate, then
that's all that is required. Basic experimentation will prove it out. If it
fails, then we ascribe causes to the failure, modify the representation to
avoid the failure, and try again. Simple iterative process. Call me naive.
The internal representation has to support certain requirements, assumptions,
dependencies, and constraints. For me my main criteria are as follows:
1. The representation needs to support activation.2. The representation needs
to support relationships (patterns among elements).
3. The representation needs to support reification.
As long as the representation does that, I'm satisfied.
~PM
Date: Tue, 4 Dec 2012 09:51:11 -0500
Subject: Re: [agi] Deb Roy: The Birth of a Word
From: [email protected]
To: [email protected]
PM: "For me knowing the brain's internal representation would be helpful, but
is not necessary,as long as a program can mimic the output using its own
internal representation. I can
use my own straw man representation and see if that works. Any representation
would do for me actually, as long as it gets results."
----------------------------------------------------------- I have no idea why
you would make a remark like this, but as I was trying to explain why it was
wrong I realized that argument was a side issue, at least partly based on
semantics, which is not very important. If you are curious about my opinions
on this I would try to explain it, but since you probably aren't I am just
going to get back on track as quickly as I can.
We certainly could write programs that could learn individual words using an
observe-interact-and-compare strategy. The problem is that as knowledge grows,
the possibilities of finding meaning and relevant actions for a particular IO
event increase to the point that it becomes impossible to search through them
all.
In other words, all evidence (or my intuition about the evidence that I have
seen) points to the necessity of using an extensive (not exhaustive but
extensive) comparative method to look at possibilities for meaning and finding
good reactions to an IO event. An AGI program cannot note every detail of an
ongoing event and use that information to perfectly denote the meaning of the
event, so it must rely on an exhaustive search of possibilities. When you have
extensive knowledge about uncountable combinations of possibilities that might
be relevant to a situation, then the program just cannot search through them
all in a reasonable amount of time. And remember, the program has to be using
some creativity as it searches through the possibilities, so some of the
possibilities that it has to consider would be functionally imaginative.
Your (would-be) AGI program can learn first words much faster than a baby.
The problem is that we don't have any good strategies of producing more
complex levels of recognition and reaction that can be used effectively.
Perhaps I am wrong about this and perhaps I do have a good strategy in mind
that might actually work to some degree. It is just that I don't feel that is
too likely. But maybe I should try some of my ideas out just to see what
happens.
Jim On Tue, Dec 4, 2012 at 2:50 AM, Piaget Modeler
<[email protected]> wrote:
The way I view it these days is that a particular set of schemes (or solutions
as I call them)
are activated and differentiated over this time period: the period it takes
for "gaa" to transform into "water" during sessions of primary circular
reactions (the infant hearing
his own voice and deciding to have it match his caregiver's pronunciation) or
secondary circular reactions (the infant getting the caregiver to say "water").
For me knowing the brain's internal representation would be helpful, but is
not necessary,as long as a program can mimic the output using its own internal
representation. I can
use my own straw man representation and see if that works. Any representation
would do for me actually, as long as it gets results.
~PM
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